About

Computer vision, OCR, biometrics, security and encryption, multi-expert fusion, document modelling.

Research interests


Publications

Showing 50 of 73 total publications in the Kent Academic Repository. View all publications.

Article

  • Yang, S., Hoque, S. and Deravi, F. (2019). Improved time-frequency features and electrode placement for EEG-based biometric person recognition. IEEE Access [Online] 7:49604-49613. Available at: http://dx.doi.org/10.1109/ACCESS.2019.2910752.
    This work introduces a novel feature extraction method for biometric recognition using EEG data and provides an analysis of the impact of electrode placements on performance. The feature extraction method is based on the wavelet transform of the raw EEG signal. The logarithms of wavelet coefficients are further processed using the discrete cosine transform (DCT). The DCT coefficients from each wavelet band are used to form the feature vectors for classification. As an application in the biometrics scenario, the effectiveness of the electrode locations on person recognition is also investigated, and suggestions are made for electrode positioning to improve performance. The effectiveness of the proposed feature was investigated in both identification and verification scenarios. Identification results of 98.24% and 93.28% were obtained using the EEG Motor Movement/Imagery Dataset (MM/I) and the UCI EEG Database Dataset respectively, which compares favorably with other published reports while using a significantly smaller number of electrodes. The performance of the proposed system also showed substantial improvements in the verification scenario when compared with some similar systems from the published literature. A multi-session analysis is simulated using with eyes open and eyes closed recordings from the MM/I database. It is found that the proposed feature is less influenced by time separation between training and testing compared with a conventional feature based on power spectral analysis.
  • Ali, A., Hoque, S. and Deravi, F. (2018). Gaze Stability for Liveness Detection. Pattern Analysis and Applications [Online] 21:437-449. Available at: http://dx.doi.org/10.1007/s10044-016-0587-2.
    Spoofing attacks on biometric systems are one of the major impediments to their use for secure unattended applications. This paper explores features for face liveness detection based on tracking the gaze of the user. In the proposed approach, a visual stimulus is placed on the display screen, at apparently random locations, which the user is required to follow while their gaze is measured. This visual stimulus appears in such a way that it repeatedly directs the gaze of the user to specific positions on the screen. Features extracted from sets of collinear and colocated points are used to estimate the liveness of the user. Data is collected from genuine users tracking the stimulus with natural head/eye movements and impostors holding a photograph, looking through a 2D mask or replaying the video of a genuine user. The choice of stimulus and features are based on the assumption that natural head/eye coordination for directing gaze results in a greater accuracy and thus can be used to effectively differentiate between genuine and spoofing attempts. Tests are performed to assess the effectiveness of the system with these features in isolation as well as in combination with each other using score fusion techniques. The results from the experiments indicate the effectiveness of the proposed gaze-based features in detecting such presentation attacks.
  • Yang, S., Deravi, F. and Hoque, S. (2016). Task sensitivity in EEG biometric recognition. Pattern Analysis and Applications [Online] 21:105-117. Available at: http://dx.doi.org/10.1007/s10044-016-0569-4.
    This work explores the sensitivity of electroencephalographic-based biometric recognition to the type of tasks required by subjects to perform while their brain activity is being recorded. A novel wavelet-based feature is used to extract identity information from a database of 109 subjects who performed four different motor movement/imagery tasks while their data was recorded. Training and test of the system was performed using a number of experimental protocols to establish if training with one type of task and tested with another would significantly affect the recognition performance. Also, experiments were conducted to evaluate the performance when a mixture of data from different tasks was used for training. The results suggest that performance is not significantly affected when there is a mismatch between training and test tasks. Furthermore, as the amount of data used for training is increased using a combination of data from several tasks, the performance can be improved. These results indicate that a more flexible approach may be incorporated in data collection for EEG-based biometric systems which could facilitate their deployment and improved performance.
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2013). A Colour Iris Recognition System Employing Multiple Classifier Techniques. ELCVIA Electronic Letters on Computer Vision and Image Analysis [Online] 12:54-65. Available at: http://elcvia.cvc.uab.es/article/view/520.
    The randomness of iris texture has allowed researchers to develop biometric systems with almost flawless accuracies. However, a common drawback of the majority of existing iris recognition systems is the constrained environment in which the user is enroled and recognized. The iris recognition systems typically require a high quality iris image captured under near infrared illumination. A desirable property of an iris recognition system is to be able to operate on colour images, whilst maintaining a high accuracy. In the present work we propose an iris recognition methodology which is designed to cope with noisy colour iris images. There are two main contributions of this paper: first, we adapt standard iris features proposed in literature for near infrared images by applying a feature selection method on features extracted from various colour channels; second, we introduce a Multiple Classifier System architecture to enhance the recognition accuracy of the biometric system. With a feature size of only 360 real valued components, the proposed iris recognition system performs with a high accuracy on UBIRISv1 dataset, in both identification and verfication scenarios.
  • Radu, P., Sirlantzis, K., Howells, G., Deravi, F. and Hoque, S. (2013). A review of information fusion techniques employed in iris recognition systems. International Journal of Advanced Intelligence Paradigms [Online] 4:211-240. Available at: http://dx.doi.org/10.1504/IJAIP.2012.052067.
    Iris recognition has shown to be one of the most reliable biometric authentication methods. The majority of iris recognition systems which have been developed require a constrained environment to enrol and recognise the user. If the user is not cooperative or the capture environment changes then the accuracy of the iris recognition system may decrease significantly. To minimise the effect of such limitations, possible solutions include the use of multiple channels of information such as using both eyes or extracting more iris feature types and subsequently employing an efficient fusion method. In this paper, we present a review of iris recognition systems using information from multiple sources that are fused in different ways or at different levels. A categorisation of the iris recognition systems incorporating multiple classifier systems is also presented. As a new desirable dimension of a biometric system, besides those proposed in the literature, the mobility of such a system is introduced in this work. The review charts the path towards greater flexibility and robustness of iris recognition systems through the use of information fusion techniques and points towards further developments in the future leading to mobile and ubiquitous deployment of such systems.
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2011). Information Fusion for Unconstrained Iris Recognition. International Journal of Hybrid Information Technology 4:1-12.
    The majority of the iris recognition algorithms available in the literature were developed to operate on near infrared images. A desirable feature of iris recognition systems with reduced constraints such as potential operability on commonly available hardware is to work with images acquired under visible wavelength. Unlike in near infrared images, in colour iris images the pigment melanin present in the iris tissue causes the appearance of reflections, which are one of the major noise factors present in colour iris images. In this paper we present an iris recognition system which is able to cope with noisy colour iris images by employing score level fusion between different channels of the iris image. The robustness of the proposed approach is tested on three colour iris images datasets, ranging from images captured with professional cameras in both constrained environment and less cooperative scenario, and finally to iris images acquired with a mobile phone.
  • McConnon, G., Deravi, F., Hoque, S., Sirlantzis, K. and Howells, G. (2011). An Investigation of Quality Aspects of Noisy Colour Images for Iris Recognition. International Journal of Signal Processing, Image Processing and Pattern Recognition [Online] 4:165-178. Available at: http://www.sersc.org/journals/IJSIP/vol4_no3.php.
    The UBIRIS.v2 dataset is a set of noisy colour iris images designed to simulate visible wavelength iris acquisition at-a-distance and on-the-move. This paper presents an examination of some of the characteristics that can impact the performance of iris recognition in the UBIRIS.v2 dataset. This dataset consists of iris images in the visible wavelength and was designed to be noisy. The quality and characteristics of these images are surveyed by examining seven different channels of information extracted from them: red, green, blue, intensity, value, lightness, and luminance. We present new quality metrics to assess the image characteristics with regard to focus, entropy, reflections, pupil constriction and pupillary boundary contrast. The results clearly suggest the existence of different characteristics for these channels and could be exploited for use in the design and evaluation of iris recognition systems.
  • Hoque, S., Azhar, M. and Deravi, F. (2011). ZOOMETRICS - Biometric Identification of Wildlife using Natural Body Marks. International Journal of Bio-Science and Bio-Technology 3:45-53.
    Using physiological or behavioral characteristics to identify humans has been in use for quite some time now. Many wildlife animals also show distinctive natural body marks that can be used to identify them individually. Scientists in conservation research often use this approach but the process is manual and can be slow and error prone. This paper reports on an investigation to use biometric techniques for the identification of an important endangered species – The Great Crested Newt. The paper reports on novel techniques for extraction of the belly patterns of these animals as a source of biometric information. Features and classification techniques used for their automatic recognition are presented. The proposed approach is tested on a database of newts under investigation by conservationists. Preliminary studies are also reported on the ageing effects when belly images are compared over a number of years. The results suggest that such biometric techniques may be suitable for developing effective and flexible identification of wildlife in the field.
  • Sirlantzis, K., Hoque, S. and Fairhurst, M. (2008). Diversity in multiple classifier ensembles based on binary feature quantisation with application to face recognition. Applied Soft Computing [Online] 8:437-445. Available at: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6W86-4N919HX-4&_user=125871&_rdoc=1&_fmt=&_orig=search&_sort=d&view=c&_acct=C000010239&_version=1&_urlVersion=0&_userid=125871&md5=65de7ea4b9a8b9f9dd824973e90ec1c4.
    In this paper we present two methods to create multiple classifier systems based on an initial transformation of the original features to the binary domain and subsequent decompositions (quantisation). Both methods are generally applicable although in this work they are applied to grey-scale pixel values of facial images which form the original feature domain. We further investigate the issue of diversity within the generated ensembles of classifiers which emerges as an important concept in classifier fusion and propose a formal definition based on statistically independent classifiers using the kappa statistic to quantitatively assess it. Results show that our methods outperform a number of alternative algorithms applied on the same dataset, while our analysis indicates that diversity among the classifiers in a combination scheme is not sufficient to guarantee performance improvements. Rather, some type of trade off seems to be necessary between participant classifiers' accuracy and ensemble diversity in order to achieve maximum recognition gains.
  • Hoque, S., Fairhurst, M., Howells, G. and Deravi, F. (2005). Feasibility of Generating Biometric Encryption Keys. Electronics Letters [Online] 41:309-311. Available at: https://doi.org/doi:10.1049/el:20057524.

Book section

  • O’Brien, J., Hoque, S., Mulvihill, D. and Sirlantzis, K. (2017). Automated Cell Segmentation of Fission Yeast Phase Images - Segmenting Cells from Light Microscopy Images. In: Silveira, M., Fred, A., Gamboa, H. and Vaz, M. eds. Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies. Scitepress, pp. 92-99. Available at: http://dx.doi.org/10.5220/0006149100920099.
    Robust image analysis is an important aspect of all cell biology studies. The geometrics of cells are critical for developing an understanding of biological processes. Time constraints placed on researchers lead to a narrower focus on what data are collected and recorded from an experiment, resulting in a loss of data. Currently, preprocessing of microscope images is followed by the utilisation and parameterisation of inbuilt functions of various softwares to obtain information. Using the fission yeast, Schizosaccharomyes pombe, we propose a novel, fully automated, segmentation software for cells with a significantly lower rate of segmentation errors than PombeX with the same dataset.
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2013). A Multi-algorithmic Colour Iris Recognition System. In: Soft Computing Applications Proceedings of the 5th International Workshop Soft Computing Applications (SOFA). Berlin, Germany: Springer, pp. 45-56. Available at: http://dx.doi.org/10.1007/978-3-642-33941-7_7.
    The reported accuracies of iris recognition systems are generally higher on near infrared images than on colour RGB images. To increase a colour iris recognition system’s performance, a possible solution is a multialgorithmic approach with an appropriate fusion mechanism. In the present work, this approach is investigated by fusing three algorithms at the score level to enhance the performance of a colour iris recognition system. The contribution of this paper consists of proposing 2 novel feature extraction methods for colour iris images, one based on a 3-bit encoder of the 8 neighborhood and the other one based on gray level co-occurrence matrix. The third algorithm employed uses the classical Gabor filters and phase encoding for feature extraction. A weighted average is used as a matching score fusion. The efficiency of the proposed iris recognition system is demonstrated on UBIRISv1 dataset.
  • Azhar, M., Hoque, S. and Deravi, F. (2012). Automatic identification of wildlife using local binary patterns. In: IET Conference on Image Processing (IPR 2012). IET, pp. B5-B5. Available at: http://dx.doi.org/10.1049/cp.2012.0454.
    Recognition of individuals is necessary for accurate estimation of wildlife population dynamics for effective management and conservation. Identifying individual wildlife by their distinctive body marks is one of the least invasive methods available. Although widely practiced, this method is mostly manual where newly captured images are compared with those in the library of previously captured images. The ability to do so automatically using computer vision techniques can improve speed and accuracy, facilitate on-field matching, and so on. This paper reports the results of using a texture based image feature descriptor, the Local Binary Patterns (LBP), for the automatic identification of an important endangered species — The Great Crested Newt (GCN). The proposed approach is tested on a database of newts' distinctive belly images which are treated as a source of biometric information. Results indicate that when both appearance and spatial information of newt belly patterns are encoded into a composite LBP feature vector, the discriminating power of the system can improve significantly.
  • Ali, A., Deravi, F. and Hoque, S. (2012). Liveness Detection Using Gaze Collinearity. In: 2012 Third International Conference on Emerging Security Technologies. IEEE, pp. 62-65. Available at: http://dx.doi.org/10.1109/EST.2012.12.
    This paper presents a liveness detection method based on tracking the gaze of the user of a face recognition system using a single camera. The user is required to follow a visual animation of a moving object on a display screen while his/her gaze is measured. The visual stimulus is designed to direct the gaze of the user to sets of collinear points on the screen. Features based on the measured collinearity of the observed gaze are then used to discriminate between live attempts at responding to this challenge and those conducted by âimpostorsâ holding photographs and attempting to follow the stimulus. An initial set of experiments is reported that indicates the effectiveness of the proposed method in detecting this class of spoofing attacks.
  • McConnon, G., Deravi, F., Hoque, S., Sirlantzis, K. and Howells, G. (2012). Impact of common ophthalmic disorders on iris segmentation. In: 2012 5th IAPR International Conference on Biometrics (ICB). IEEE, pp. 277-282. Available at: http://dx.doi.org/10.1109/ICB.2012.6199820.
    As iris recognition moves from constrained indoor and near-infrared systems towards unconstrained on-the-move and at-a-distance systems, possibly using visible light illumination, interest in measurement of the fidelity of the acquired images and their impact on recognition performance has grown. However, the impact of the subject's physiological characteristics on the nature of the acquired images has received little attention. In this paper we catalog a selection of the most common ophthalmic disorders and investigate some of their characteristics including their prevalence and possible impact on recognition performance. The paper also includes an experimental exploration of the effect of such conditions on segmentation of the iris image.
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2012). Image Enhancement vs Feature Fusion in Colour Iris Recognition. In: 2012 Third International Conference on Emerging Security Technologies. IEEE, pp. 53-57. Available at: http://dx.doi.org/10.1109/EST.2012.33.
    In iris recognition, most of the research was conducted on operation under near infrared illumination. For an iris recognition system to be deployed on common hardware devices, such as laptops or mobile phones, its ability of working with visible spectrum iris images is necessary. Two of the main possible approaches to cope with noisy images in a colour iris recognition system are either to apply image enhancement techniques or to extract multiple types of features and subsequently to employ an efficient fusion mechanism. The contribution of the present paper consists of comparing which of the two above mentioned approaches is best in both identification and verification scenarios of a colour iris recognition system. The efficiency of the two approaches is demonstrated on UBIRISv1 dataset
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2010). On Combining Information from Both Eyes to Cope with Motion Blur in Iris Recognition. In: 4th International Workshop on Soft Computing Applications. IEEE, pp. 175-181. Available at: http://dx.doi.org/10.1109/SOFA.2010.5565604.
    Iris Recognition has emerged as one of the best biometric authentication techniques in recent years. However, a significant drawback of this biometric modality is the constrained environment in which the user is enrolled and recognized. It typically requires the user to be very cooperative for good quality images to be captured. If this limitation could be effectively addressed, it would be possible to employ iris recognition in environments where images incorporating increased noise and distortions were present whilst maintaining high recognition accuracy. In the present paper, we explore how the effect of image distortions caused by motion blur may be significantly reduced by using iris information from both eyes of the user.
  • Howells, G., Selim, H., Fairhurst, M., Deravi, F. and Hoque, S. (2008). A Securable Autonomous Generalised Document Model (SAGENT). In: Stoica, A., Arslan, T., Howard, D., Higuchi, T. and El-Rayis, A. O. eds. 2008 Bio-Inspired, Learning and Intelligent Systems for Security. IEEE, pp. 136-141. Available at: http://dx.doi.org/10.1109/BLISS.2008.10.
    A generalised modelling system for handling multimedia documents is introduced capable of allowing documents authored in differing formats to be efficiently manipulated, compared and analysed. The model represents a document as a secure autonomous object possessing the ability to represent and modify its own meta data whilst not compromising the ideals of maintaining the autonomy of individual document components. The paper presents the model by means of a case study of the existing prototype implementation followed by the detailed presentation of the implementation of the model using Object-Oriented technology showing how the model is able to address the key issues of security, generality and autonomy.

Conference or workshop item

  • Ali, A., Hoque, S. and Deravi, F. (2020). Biometric Presentation Attack Detection Using Stimulated Pupillary Movements. In: 9th International Conference on Imaging for Crime Detection and Prevention (ICDP-2019). London, UK, pp. 80-85.
    Biometric systems can be subverted using presentation attack artefacts. This work presents a way to deal with the vulnerability to such spoofing attacks. In this work we propose the use of pupillary movements to detect such presentation attacks. The pupillary movements were stimulated by presentation of a moving visual challenge to ensure that some pupillary motion can be captured. Photo, 2D mask and 3D mask attack artefacts were evaluated based on data captured from 80 volunteers performing genuine attempts and spoofing attempts. The results indicate the effectiveness of the proposed pupillary movement feature to stop presentation attacks.
  • Al-Darkazali, M., Hoque, S. and Deravi, F. (2020). Spatial Signatures for EEG-based Biometric Person Recognition. In: 9th International Conference on Imaging for Crime Detection and Prevention (ICDP-2019). pp. 68-73.
    Biometric person recognition using EEG signals has received considerable attention in recent years. This paper proposes a new feature based on the co-activation of EEG sensors. A visual representation of this co-activation feature is used to illustrate the identity-bearing nature of the proposed feature. The DEAP database was used to evaluate the proposed feature which was presented in the form of a visual signature indicating the spatial correlations around the scalp of EEG signals for an individual. The results show a high identification accuracy irrespective of the emotional state of the data subjects.
  • Alsufyani, H., Hoque, S. and Deravi, F. (2019). Usability of Skin Texture Biometrics for Mixed-Resolution Images. In: Eighth IEEE International Conference on Emerging Security Technologies. IEEE. Available at: https://doi.org/10.1109/EST.2019.8806212.
    There is a growing demand for alternative biometric modalities that can handle various real world challenges such as recognising partially occluded individuals. Skin texture has been proposed as a potential alternative; however, such skin texture analysis can become difficult when captured images are at varying resolutions (due to different distances or devices). This paper explores the prospect of using mixed-resolution facial skin images as a source of biometric information. The four facial skin regions investigated here are the forehead, right cheek, left cheek, and chin which were selected because at least one of these are expected to be captured in real-world scenarios. The proposed framework first localises and assesses the usability of the extracted region of interest (ROI) for subsequent analysis. Local Binary Pattern (LBP) descriptors are then used for feature matching because of their reported effectiveness in extracting skin texture information. Experiments conducted using the XM2VTS database suggest that mixed resolution skin texture images can provide adequate information for biometric applications.
  • Ali, A., Alsufyani, N., Hoque, S. and Deravi, F. (2019). Gaze-based Presentation Attack Detection for Users Wearing Tinted Glasses. In: 2019 Eighth International Conference on Emerging Security Technologies (EST). IEEE, pp. 1-5. Available at: https://doi.org/10.1109/EST.2019.8806201.
    Biometric authentication is vulnerable to presentation (spoofing) attacks. It is important to address the security vulnerability of spoofing attacks where an attacker uses an artefact presented at the sensor to subvert the system. Gaze-tracking has been proposed for such attack detection. In this paper, we explore the sensitivity of a gaze-based approach to spoofing detection in the presence of eye-glasses that may impact detection performance. In particular, we investigate the use of partially tinted glasses such as may be used in hazardous environments or outdoors in mobile application scenarios The attack scenarios considered in this work include the use of projected photos, 2D and 3D masks. A gaze-based spoofing detection system has been extensively evaluated using data captured from volunteers performing genuine attempts (with and without wearing such tinted glasses) as well as spoofing attempts using various artefacts. The results of the evaluations indicate that the presence of tinted glasses has a small impact on the accuracy of attack detection, thereby making the use of such gaze-based features possible for a wider range of applications.
  • Alsufyani, H., Hoque, S. and Deravi, F. (2019). Usability of Skin Texture Biometrics for Mixed-Resolution Images. In: 2019 Eighth International Conference on Emerging Security Technologies (EST). IEEE, pp. 1-6. Available at: https://doi.org/10.1109/EST.2019.8806212.
    There is a growing demand for alternative biometric modalities that can handle various real-world challenges such as recognizing partially occluded individuals. Skin texture has been proposed as a potential alternative; however, such skin texture analysis can become difficult when captured images are at varying resolutions (due to different distances or devices). This paper explores the prospect of using mixed-resolution facial skin images as a source of biometric information. The four facial skin regions investigated here are the forehead, right cheek, left cheek, and chin which were selected because at least one of these are expected to be captured in real-world scenarios. The proposed framework first localises and assesses the usability of the extracted region of interest (ROI) for subsequent analysis. Local Binary Pattern (LBP) descriptors are then used for feature matching because of their reported effectiveness in extracting skin texture information. Experiments conducted using the XM2VTS database suggest that mixed resolution skin texture images can provide adequate information for biometric applications.
  • Ali, A., Alsufyani, N., Hoque, S. and Deravi, F. (2019). Gaze-based Presentation Attack Detection for Users Wearing Tinted Glasses. In: Eighth International Conference on Emerging Security Technologies (EST). IEEE. Available at: https://doi.org/10.1109/EST.2019.8806201.
    Biometric authentication is vulnerable to presentation (spoofing) attacks. It is important to address the security vulnerability of spoofing attacks where an attacker uses an artefact presented at the sensor to subvert the system. Gaze-tracking has been proposed for such attack detection. In this paper, we explore the sensitivity of a gaze-based approach to spoofing detection in the presence of eye-glasses that may impact detection performance. In particular, we investigate the use of partially tinted glasses such as may be used in hazardous environments or outdoors in mobile application scenarios The attack scenarios considered in this work include the use of projected photos, 2D and 3D masks. A gaze-based spoofing detection system has been extensively evaluated using data captured from volunteers performing genuine attempts (with and without wearing such tinted glasses) as well as spoofing attempts using various artefacts. The results of the evaluations indicate that the presence of tinted glasses has a small impact on the accuracy of attack detection, thereby making the use of such gaze-based features possible for a wider range of applications.
  • Alsufyani, N., Ali, A., Hoque, S. and Deravi, F. (2018). Biometric Presentation Attack Detection using Gaze Alignment. In: 2018 IEEE 4th International Conference on Identity, Security, and Behavior Analysis (ISBA). IEEE. Available at: https://dx.doi.org/10.1109/ISBA.2018.8311472.
    Face recognition systems have been improved rapidly in recent decades. However, their wide deployment has been hindered by their vulnerability to spoofing attacks. In this paper, we present a challenge and response method to detect attack in face recognition systems by recording the gaze of a user in response to a moving stimulus. The proposed system extracts eye centres in the captured frames and computes features from these landmarks to ascertain whether the gaze aligns with the challenge trajectory in order to detect spoofing attacks. The system is tested using a new database simulating mobile device use with 70 subjects attempting three types of spoof attacks (projected photo, looking through a 2D mask or wearing a 3D mask). Evaluations on the collected database show that the proposed approach performs favourably when compared with state-of-the-art methods.
  • Alsufyani, H., Hoque, S. and Deravi, F. (2017). Automated Skin Region Quality Assessment for Texture-based Biometrics. In: 2017 Seventh International Conference on Emerging Security Technologies (EST). IEEE, pp. 169-174. Available at: https://doi.org/10.1109/EST.2017.8090418.
    Designing a biometric system based solely on skin texture is of interest because the face is sometimes occluded by hair or artefacts in many real-world contexts. This work presents a novel framework for the assessment of skin-based biometric systems incorporating skin quality information. The quality or purity of the extracted skin region is automatically established using pixel colour models prior to biometric processing. Facial landmarks are detected to facilitate automated extraction of facial regions of interest. Although the present study is confined to the forehead region, the idea can be extended to other skin regions. Local Binary Patterns (LBP) and Gabor wavelet filters are utilised to extract skin features. Using the publicly available XM2VTS database, the experimental results show that the system provides promising performance when compared to other commonly used techniques.
  • Ali, A., Alsufyani, N., Hoque, S. and Deravi, F. (2017). Biometric Counter-spoofing for Mobile Devices using Gaze Information. In: 7th International Conference on Pattern Recognition and Machine Intelligence. Springer, pp. 11-18. Available at: https://doi.org/10.1007/978-3-319-69900-4_2.
    With the rise in the use of biometric authentication on mobile devices, it is important to address the security vulnerability of spoofing attacks where an attacker using an artefact representing the biometric features of a genuine user attempts to subvert the system. In this paper, techniques for presentation attack detection are presented using gaze information with a focus on their applicability for use on mobile devices. Novel features that rely on directing the gaze of the user and establishing its behaviour are explored for detecting spoofing attempts. The attack scenarios considered in this work include the use of projected photos, 2D and 3D masks. The proposed features and the systems based on them were extensively evaluated using data captured from volunteers performing genuine and spoofing attempts. The results of the evaluations indicate that gaze-based features have the potential for discriminating between genuine attempts and imposter attacks on mobile devices.
  • Alsufyani, H., Hoque, S. and Deravi, F. (2016). Exploring the Potential of Facial Skin Regions for the Provision of Identity Information. In: The 7th IET International Conference on Imaging for Crime Detection and Prevention (ICDP-16). IET. Available at: http://dx.doi.org/10.1049/ic.2016.0084.
    This work presents a novel framework to investigate the possibility of using texture information from facial skin regions for biometric person recognition. Such information will be practically useful when the entire facial image is not available for identifying the individuals. Four facial regions have been investigated (i.e. forehead, right cheek, left cheek, and chin) since they are relatively easy to distinguish in frontal images. Facial landmarks are automatically detected to facilitate the extraction of these facial regions of interest. A new skin detection technique is applied to identify regions with significant skin content. Each such skin regions are then processed independently using features based on Local Binary Patterns and Gabor wavelet filters. Feature fusion is then used prior to classification of the images. Experiments were carried out using the publicly available Skin Segmentation database and the XM2VTS databases to evaluate the skin detection technique and the biometric recognition performances respectively. The results indicate that the skin detection algorithm provided an acceptable results when compared with other state-of-the-art skin detection algorithms. In addition, the forehead and the chin regions where found to provide a rich source of biometric information.
  • Yassin, D., Hoque, S. and Deravi, F. (2016). FACE RECOGNITION ACROSS AGES. In: 6th Brunei International Conference on Engineering and Technology 2016 (BICET2016).
    This paper is concerned with the effect of ageing on biometric systems and particularly its impact on face recognition systems. Being biological tissue in nature, facial biometric trait undergoes significant changes as a person ages. Consequently, developing biometric applications for long-term use becomes a particularly challenging task. The idea behind the investigation presented here is that biometric systems have uneven difficulty in recognising people from different ages. Some algorithms may perform better for certain age groups. Therefore, a carefully optimised multi-algorithmic system can reduce the error rates. A subset of 100 subjects from the MORPH-II database has been selected to test the performance of a face verification system. The population is split into 5 age bands (?19, 20-29, 30-39, 40-49, ?50 years) based on their age during enrolment. The facial image database used in the experiments here contains images acquired over a period of five years. In the proposed multi-classifier scheme, features extracted from face images are transformed by different projection algorithms prior to matching. It has been observed that all the age groups showed improved performances when compared to the single classifier error rates. Of all the groups, the EER were highest for the younger population (?19 year olds).
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2013). Optimizing 2D Gabor Filters for Iris Recognition. In: 4th International Conference on Emerging Security Technologies (EST 2013),. IEEE, pp. 47-50. Available at: http://dx.doi.org/10.1109/EST.2013.15.
    The randomness and richness present in the iris texture make the 2D Gabor filter bank analysis a suitable technique to be used for iris recognition systems. To accurately characterize complex texture structures using 2D Gabor filters it is necessary to use multiple sets of parameters of this type of filters. This paper proposes a technique of optimizing multiple sets of 2D Gabor filter parameters to gradually enhance the accuracy of an iris recognition system. The proposed methodology is suitable to be applied on both near infrared and visible spectrum iris images. To illustrate the efficiency of the filter bank design technique, UBIRISv1 database was used for benchmarking
  • Ali, A., Deravi, F. and Hoque, S. (2013). Directional Sensitivity of Gaze-Collinearity Features in Liveness Detection. In: Emerging Security Technologies (EST), 2013 Fourth International Conference on. pp. 8-11. Available at: http://dx.doi.org/10.1109/EST.2013.7.
    To increase the trust in using face recognition systems, these need to be capable of differentiating between face images captured from a real person and those captured from photos or similar artifacts presented at the sensor. Methods have been published for face liveness detection by measuring the gaze of a user while the user tracks an object on the screen, which appears at pre-defined, places randomly. In this paper we explore the sensitivity of such a system to different stimulus alignments. The aim is to establish whether there is such sensitivity and if so to explore how this may be exploited for improving the design of the stimulus. The results suggest that collecting feature points along the horizontal direction is more effective than the vertical direction for liveness detection.
  • Yassin, D., Hoque, S. and Deravi, F. (2013). Age Sensitivity of Face Recognition Algorithms. In: 4th International Conference on Emerging Security Technologies (EST 2013),. pp. 12-15. Available at: http://dx.doi.org/10.1109/EST.2013.8.
    This paper investigates the performance degradation of facial recognition systems due to the influence of age. A comparative analysis of verification performance is conducted for four subspace projection techniques combined with four different distance metrics. The experimental results based on a subset of the MORPH-II database show that the choice of subspace projection technique and associated distance metric can have a significant impact on the performance of the face recognition system for particular age groups.
  • Ali, A., Deravi, F. and Hoque, S. (2013). Spoofing attempt detection using gaze colocation. In: Biometrics Special Interest Group (BIOSIG), 2013 International Conference. pp. 1-12.
    Spoofing attacks on biometric systems are one of the major impediments to their use for secure unattended applications. This paper presents a novel method for face liveness detection by tracking the gaze of the user with an ordinary webcam. In the proposed system, an object appears randomly on the display screen which the user is required to look at while their gaze is measured. The visual stimulus appears in such a way that it repeatedly directs the gaze of the user to specific points on the screen. Features extracted from images captured at these sets of colocated points are used to estimate the liveness of the user. A scenario is investigated where genuine users track the challenge with head/eye movements whereas the impostors hold a photograph of the target user and attempt to follow the stimulus during simulated spoofing attacks. The results from the experiments indicate the effectiveness of the gaze colocation feature in detecting spoofing attack
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2013). A Novel Iris Clustering Approach Using LAB Color Features. In: 4th IEEE International Symposium on Electrical And Electronics Engineering (ISEEE 2013). IEEE, pp. 1-4. Available at: http://dx.doi.org/10.1109/ISEEE.2013.6674362.
    Interesting results of color clustering for the iris images in the UBIRISv1 database are presented. The iris colors are characterized by feature vectors with 80 components corresponding to histogram bins computed in the CIELAB color space. The feature extraction is applied to the first session eye images after undergoing an iris segmentation process. An agglomerative hierarchical algorithm is used to organize 1.205 segmented iris images in 8 clusters based on their color content.
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2012). A Visible Light Iris Recognition System using Colour Information. In: 9th IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA 2012). Acta Press. Available at: http://dx.doi.org/10.2316/P.2012.778-019.
    The iris has been shown to be a highly reliable biometric modality with almost perfect authentication accuracy. However, a classical iris recognition system operates under near infrared illumination, which is a major constraint for a range of applications. In this paper, we propose an iris recognition system which is able to cope with noisy colour iris images by employing image processing techniques together with a Multiple Classifier System to fuse the information from various colour channels. There are two main contributions in the present work: first, we adapt standard iris features, proposed in the literature for near infrared images, to match the characteristics of colour iris images; second, we introduce a robust fusion mechanism to combine the features from various colour channels. With a feature size of only 360 real numbers, the efficiency of the proposed biometric system is demonstrated on the UBIRISv1 dataset for both identification and verification scenarios.
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2011). A Versatile Iris Segmentation Algorithm. In: 2011 BIOSIG Conference on Biometrics and Security.
  • Radu, P., Sirlantzis, K., Howells, G., Deravi, F. and Hoque, S. (2011). Information Fusion for Unconstrained Iris Recognition. In: International Conference on Emerging Security Technologies (EST 2011).
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2010). Are Two Eyes Better Than One?. In: International Conference on Emerging Security Technologies (EST 2010).
  • Sirlantzis, K., Howells, G., Deravi, F., Hoque, S., Radu, P., McConnon, G., Savatier, X., Ertaud, J., Ragot, N., Dupuis, Y. and Iraqui, A. (2010). Nomad Biometric Authentificatin (NOBA): Towards Mobile and Ubiquitous Person Identification. In: International Conference on Emergy Security Technologies (EST 2010).
  • Radu, P., Sirlantzis, K., Howells, G., Hoque, S. and Deravi, F. (2010). Can Dual Iris Help with Motion Blur?. In: 4th IEEE Int. Workshop on Soft Computing Applications (SOFA2010).
  • McConnon, G., Deravi, F., Hoque, S., Howells, G. and Sirlantzis, K. (2010). A Novel Interactive Biometric Passport Photograph Alignment System. In: 18th European Symposium on Artificial Neural Networks (ESANN).
  • McConnon, G., Deravi, F., Hoque, S., Sirlantzis, K. and Howells, G. (2010). A Survey of Point-Source Specular Reflections in Noisy Iris Images. In: Emerging Security Technologies (EST), 2010 International Conference. pp. 13-17. Available at: http://dx.doi.org/10.1109/EST.2010.33.
    This paper presents an examination of a selection of images taken from the UBIRIS.v2 dataset to explore the characteristics of point-source reflections present in the images. These reflections were some of the most commonly found sources of noise in iris images acquired under visual wavelength light and clearly impact the accuracy of iris recognition systems. The spatial and intensity distributions of these reflections is studied and results are presented that can be used to model their behaviour. This information can be helpful for developing more accurate iris synthesis techniques and for the study of iris image focus assessment as well as developing better matching algorithms for iris recognition.
  • Hoque, S., Fairhurst, M. and Howells, G. (2008). Evaluating Biometric Encryption Key Generation using Handwritten Signatures. In: 2008 ECSIS Symposium on Bio-Inspired, Learning and Intelligent Systems for Security (BLISS 2008). IEEE Computer Socieity, pp. 17-22.
    In traditional cryptosystems, user authentication is based on the possession of secret keys/tokens. Such keys can be forgotten, lost, stolen, or may be illegally shared, but an ability to relate a ctyptographic key to biometric data can enhance the trustworthiness of a system. In this paper, we demonstrate how biometric keys can be generated directly from live biometrics, under certain conditions, by partitioning feature space into subspaces and partitioning these into cells, where each cell subspace contributes to the overall key generated. We evaluate the proposed scheme on real biometric data, representing both genuine samples and attempted imitations. Experimental results then demonstrate the extent to which the proposed technique can be implemented reliably in possible practical scenarios
  • Osoka, A., Fairhurst, M. and Hoque, S. (2007). A Novel Approach to Quantifying Risk in Biometric Systems Performance. In: Proc. 4th Visual Engineering (VIE) Conference.
  • Hoque, S. and Fairhurst, M. (2006). A Novel Scheme for Implementation of the Scanning nTuple Classifier in a Constrained Environment. In: Proc. 10th International Workshop on Frontiers in Handwriting Recognition (IWFRH). pp. 127-132.
    The scanning ntuple classifier is an efficient and accurate classifier for handwriting recognition. One of the major difficulties in implementing this scheme is its demand for a very large memory space, thus making it unsuitable for resource constrained systems such as embedded applications. This paper proposes some modifications to the basic sntuple algorithm which eliminates the necessity of normalizing the chain-code length, by adjusting the memory cell increments as an inverse function the chain length. The resulting system performance is shown to be superior to the standard sntuple configuration in both speed and accuracy when smaller and fewer sntuples are used, a configuration which also reduces the demand for memory.
  • Fairhurst, M., Hoque, S. and Boyle, T. (2005). Assessing Behavioural Characteristics of Dyspraxia through on-line Drawing Analaysis. In: Proceedings of the 12th Conference of the International Graphonomics Society (IGS2005).
  • Fairhurst, M., Hoque, S., Howells, G. and Deravi, F. (2005). Evaluating Biometric Encryption Key Generation. In: Proceedings of Third Cost 275 Workshop, Biometrics on the Internet - http://www.fub.it/Cost275. pp. 93-96.
    In traditional cryptosystems, user authentication is based on
    possession of secret keys/tokens. Such keys can be forgotten,
    lost, stolen, or may be illegally shared, but an ability to relate
    a cryptographic key to biometric data can enhance the
    trustworthiness of a system. This paper presents a new
    approach to generating encryption keys directly from
    biometrics.
  • Howells, G., Selim, H., Fairhurst, M., Deravi, F. and Hoque, S. (2005). SAGENT: A Model for Exploiting Biometric-Based Security for Distributed Multimedia Documents. In: Proceedings of Third Cost 275 Workshop, Biometrics on the Internet - http://www.fub.it/Cost275.
    Issues concerning the security of heterogeneous documents in
    a distributed environment are addressed by introducing a
    novel document model capable of incorporating any desired,
    and in particular biometrically based, security techniques
    within existing documents without compromising the original
    document structure.

Thesis

  • Pg Hj Mohd Yassin, D. (2016). Novel Template Ageing Techniques to Minimise the Effect of Ageing in Biometric Systems.
    ect of ageing on biometric systems and particularly its impact on face recognition systems. Being biological tissue in nature, facial biometric trait undergoes ageing. As a result developing biometric applications for long-term use becomes a particularly challenging task. Despite the rising attention on facial ageing, longitudinal study of face recognition remains an understudied problem in comparison to facial variations due to pose, illumination and expression changes. Regardless of any adopted representation, biometric patterns are always affected by the change in the face appearance due to ageing. In order to overcome this problem either evaluation of the changes in facial appearance over time or template-age transformation-based techniques are recommended.

    By using a database comprising images acquired over a 5-years period, this thesis explores techniques for recognising face images for identify verification. A detailed
    investigation analyses the challenges due to ageing with respect to the performance
    of biometric systems. This study provides a comprehensive analysis looking at both lateral age as well as longitudinal ageing.

    This thesis also proposes novel approaches for template ageing to compensate the ageing effects for verification purposes. The approach will explore both linear and nonlinear transformation mapping methods. Furthermore, the compound effect of ageing with other variate (such as gender, age group) are systematically analysed. With the
    implementation of the novel approach, it can be seen that the GAR (Genuine Accept Rate) improved signifi
  • Ali, A. (2015). Biometric Liveness Detection Using Gaze Information.
    This thesis is concerned with liveness detection for biometric systems and in particular for face recognition systems. Biometric systems are well studied and have the potential to provide satisfactory solutions for a variety of applications.
    However, presentation attacks (spoofng), where an attempt is made at subverting them system by making a deliberate presentation at the sensor is a serious challenge to their use in unattended applications. Liveness detection techniques can help with protecting biometric systems from attacks made through the presentation of artefacts and recordings at the sensor. In this work novel techniques for liveness detection are presented using gaze information.

    The notion of natural gaze stability is introduced and used to develop a number of novel features that rely on directing the gaze of the user and establishing its behaviour. These features are then used to develop systems for detecting spoofng attempts. The attack scenarios considered in this work include the use of hand held photos and photo masks as well as video reply to subvert the system. The proposed features and systems based on them were evaluated extensively using data captured from genuine and fake attempts.

    The results of the evaluations indicate that gaze-based features can be used to discriminate between genuine and imposter. Combining features through feature selection and score fusion substantially improved the performance of the proposed features.
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