International Journal of Biometrics (7 papers in press)
Biometric Authentication System Based on Texture Features of Retinal Images
by Jarina B. Mazumdar, S.R. Nirmala
Abstract: In biometric authentication system, distinct set of characteristic features are
used to identify an authorized person. Retina is a stable biometric feature because of its location and unique physiological characteristics. In this paper, we propose a texture feature based retinal authentication system. Texture features are considered as important features for authentication purpose. These texture features of retina are extracted using Local Conguration Pattern (LCP) and Radon transform technique. The LCP computes the local structural information as well as the microscopic information of the image. Using Radon transform on retinal images, Radon features are extracted which contains the texture information of the blood vessels. A feature vector is formed by combining all theses LCP and Radon features and then fed to a Feed-forward Articial Neural
Network (FANN) classier. This stage checks whether the test image belongs to the authorized person or not. Three general retinal databases DRIVE, HRF, Messidor, and images collected from two local eye hospitals are considered to authenticate a person. Two retinal authentication databases RIDB and VARIA are also used for evaluating the performance of the system. The results obtained show that the system is effective and efficient in authenticating the individuals.
Keywords: Texture feature; LCP; Radon transform; FANN.
User Attitude towards Novel Biometric System and Usability Analysis
by Ishan Bharadwaj, Narendra D. Londhe, Sunil Kumar Kopparapu
Abstract: The advent of biometrics as a mean of authentication for financial institutes, government agencies, and personal devices caused significant acceleration in the realisation of security solutions. Increasing deployments and affordable hardware components corroborate this statement. Though passwords have commendable user convenience but suffers from serious issues which has evolved biometrics into highly secure and reliable authentication methods. Every biometric technique should be easy to learn, impel to use and user convenient. In this paper, we have proposed to analyse the usability of fingerprint dynamics by performing user preference-based experimentations. This is also followed by the study of various aspects of fingerprint dynamics as an authentication system. Results are reported for the usability trials which includes data collection from 348 participants, followed by comprehensive statistical analysis. User preferences were also measured using attitude questionnaires. As an indicator of system performance results of authentication experiments are also reported.
Keywords: Fingerprint dynamics; Biometrics; Authentication; Usability,User experience; User characteristics.
Towards Contactless Palm Region Extraction in Complex Environment
by Tingting Chai, Shenghui Wang, Dongmei Sun
Abstract: Palm region of interest (ROI) extraction is an indispensable procedure in palmprint
recognition. Prior works generally perform well on palm ROI extraction because of dedicated devices and well-controlled environment. To make hand placement less-constrained and improve usability, mobile palmprint recognition has attracted a wide attention in recent years. For mobile phone images captured in complex natural environment, palm ROI extraction is a challenging work due to varying illumination, complex background and contactless acquisition mode. In this paper, a mobile palmprint dataset (SPIC) is at first established with five smartphones, comprising
4000 images collected from 128 persons in two separate sessions. Furthermore, a novel pre-processing approach is proposed to achieve ROI extraction in mobile scenarios, which includes colour component selection, learning-based fast hand segmentation and geometry-driven valley point location. Experimental results demonstrate that the proposed method can achieve high extraction accuracy and computational efficiency on PolyU1.0, HA-BJTU and SPIC palmprint databases.
Keywords: Palm ROI extraction; palmprint recognition; hand segmentation; contour tracking;
valley point detection.
Low and High frequency Wavelet Sub-band based Feature extraction
by Rajeshwari Devi D V, Narasimha Rao K
Abstract: In a biometric system, feature extraction is an important task for faster and efficient identification of a person. A new feature extraction method, Sub-band PCA+LDA is proposed to extract distinct features from low frequency and high frequency wavelet sub-bands. The proposed method captures both local and global features of two biometrics under consideration, face and iris. The matching scores of face and iris are normalized using Minmax and Tanh techniques, and fused using Sum rule, Product rule and Weighted Sum rule. For unimodal systems, the proposed method gives better recognition rate in comparison to other existing methods, like DWT, DWT+PCA, DWT+LDA, Local binary pattern and Subspace LDA. The performance of the proposed multimodal biometric system is superior than unimodal system in terms of attaining maximum of 100% recognition rate and minimum Equal Error Rate (EER) of 0.017 for standard biometric databases.
Keywords: Multimodal Biometrics; Sub-band fusion; Feature extraction; Discrete Wavelet transform; Principal component analysis; Linear discriminant analysis; Matching score level fusion.
Offline Signature Verification Using Shape Correspondence
by Pradeep Narwade, Rajendra Sawant, Sanjiv Bonde
Abstract: Biometrics has always been an integral part of human identification and verification, with offline signature verification being a most crucial component of it. It is a challenging task as the signatures are time variant. To address the above difficulty, this paper presents a novel approach to identify the correspondence between pixels of different signatures using an adaptive weighted combination of shape context distance and Euclidean distance. These correspondences are then used for the transformation of query signature plane to reference signature plane using thin plate spline transformation. The distances between signatures are computed using plane transformation, a shape descriptor, and the farness between matched pixels. The computed distances are then fed to the Support Vector Machine (SVM) classifier to determine the merit of genuineness. With the proposed methodology, better accuracy is obtained. The results exhibit an accuracy of 89.58% using proposed method on GPDS synthetic signature database.
Keywords: Handwritten signature verification; Pattern recognition; Pattern analysis; Shape matching; Thin plate spline transformation; Shape context; Document analysis.
Forensic Dental Biometry A Human Identification System Using Panoramic Dental Radiographs Based on Shape of Mandibular Bone
by Mahroosh Banday, Ajaz Hussain Mir
Abstract: Dental Biometrics is a new and growing area of Forensic Biometrics that uses the unique features of dental structures from dental radiographs to automatically establish a persons identity from their dental remains when the conventional biometric features are not available. In this paper, we present a new and efficient approach for identifying people, by using the structure of mandible from the panoramic dental radiographs as a biometric identifier. The system automatically segments the mandible from dental panoramic images to extract the representative feature vectors for each mandible, which are later used for matching and identification. The experimental results of the proposed system using a database of 120 ante-mortem and 90 post-mortem panoramic dental images show that the system is robust and effective in identifying individuals and exhibits a high Recognition rate (RR) up to 98.79%, low Equal error rate (ERR) of 1.5% and a remarkable identification performance.
Keywords: Dental Biometrics; Odontology; Forensic identification; Mandible; Dental radiographs.
Fusion of Hand-shape and Palm-print Traits using Morphology for Bi-modal Biometric Authentication
by Wen-Shiung Chen, Wei-Chang Wang
Abstract: This paper presents a bimodal biometric recognition technique fusing hand-shape and palm-print traits of a human hand for personal authentication. In this fusion scheme, a novel feature extraction based on morphology, called broken mirror method, is designed and a two-stage recognition is proposed. We utilize the image morphology and concept of Voronoi diagram to slice the image of the front of the whole palm into several strips in which each strip is then decomposed into irregular blocks in accordance with the hand geometry. Furthermore, statistic characteristics of the gray level in each of the blocks is employed as characteristic values. In the final stage, a coarse recognition followed by a fine recognition will be adopted to recognize the identity. The experimental results show that the proposed biometric fusion system has an encouraging performance on recognition. The false acceptance rate (FAR) and false rejection rate (FRR) are reduced efficiently down to 0.0035% and 5.7692%, respectively. Our approach achieves the EER of about 7% which is better than that of other methods.
Keywords: Personal Authentication; Biometric Recognition; Multimodal Biometrics; Bimodal; Hand-shape; Palm-print; Morphology.