Age Sensitivity of Face Recognition Algorithms

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

Comparison of Iris Recognition between Active Contour and Hough Transform

Research in iris recognition has been explosive in recent years. There are a few fundamental issues in iris recognition such as iris acquisition, iris segmentation, texture analysis and matching analysis that has been brought up. In this paper, we focus on a fundamental issue in iris segmentation which is segmentation accuracy. The accuracy of iris segmentation can be negatively affected because of poor segmentation of iris boundary. Iris boundary might have unsmooth, poor and unclear edges. Because of that, a method that can segment this type of boundary needs to be developed. A method based on active contour is proposed not only to increase the segmentation accuracy, but also to increase the recognition accuracy. The proposed method is compared with the modified Hough Transform method to observe the performance of both methods. Iris images from CASIA v4 are used for our experiment. According to results, the proposed method is better than the modified Hough Transform method in terms of segmentation accuracy, recognition accuracy and implementation time. This shows that the proposed method is more accurate than the Hough Transform method

A Fingerprint Matching Model using Unsupervised Learning Approach

The increase in the number of interconnected information systems and networks to the Internet has led to an increase in different security threats and violations such as unauthorised remote access. The existing network technologies and communication protocols are not well designed to deal with such problems. The recent explosive development in the Internet allowed unwelcomed visitors to gain access to private information and various resources such as financial institutions, hospitals, airports ... etc. Those resources comprise critical-mission systems and information which rely on certain techniques to achieve effective security. With the increasing use of IT technologies for managing information, there is a need for stronger authentication mechanisms such as biometrics which is expected to take over many of traditional authentication and identification solutions. Providing appropriate authentication and identification mechanisms such as biometrics not only ensures that the right users have access to resources and giving them the right privileges, but enables cybercrime forensics specialists to gather useful evidence whenever needed. Also, critical-mission resources and applications require mechanisms to detect when legitimate users try to misuse their privileges; certainly biometrics helps to provide such services. This paper investigates the field of biometrics as one of the recent developed mechanisms for user authentication and evidence gathering despite its limitations. A biometric-based solution model is proposed using various statistical-based unsupervised learning approaches for fingerprint matching. The proposed matching algorithm is based on three various similarity measures, Cosine similarity measure, Manhattan distance measure and Chebyshev distance measure. In this paper, we introduce a model which uses those similarity measures to compute a fingerprint’s matching factor. The calculated matching factor is based on a certain threshold value which could be used by a forensic specialist for deciding whether a suspicious user is actually the person who claims to be or not. A freely available fingerprint biometric SDK has been used to develop and implement the suggested algorithm. The major findings of the experiments showed promising and interesting results in terms of the performance of all the proposed similarity measures.Final Accepted Versio

Broken Symmetries, Random Morphogenesis, and Biometric Distance

This paper discusses the role of symmetry-breaking in biometric recognition. Using publicly available databases, we investigate three kinds of broken symmetries in iris patterns: binocular, monocular, and monozygotic. We report a small but statistically significant difference in similarities between the ipsilateral and the contralateral eyes of twins, and also between genetically identical and nonidentical eyes. Another new finding is a doubling in the variance of Hamming distance scores under a simple monocular mirror transformation, which is consistent with an assessment of entropy

CHARACTERIZING HABITUATION USING THE TIME-ON-TASK METRIC IN AN IRIS RECOGNITION SYSTEM

This thesis presents a characterization of biometric habituation in an iris recognition study using qualitative analysis of a distributed habituation survey and quantitative analysis of iris images collected in 2010 and 2012. The performed analyses answered the following two questions: a) How consistently does the biometric community define habituation?; and b) Does the time-on-task variable provide enough evidence to indicate the existence of habituation in an iris recognition system? The qualitative analysis examined responses to 12 habituation-related questions from 13 biometric experts to identify common themes that not only determined definition consistency but also characterized critical components often omitted from habituation definitions. Upon completion of the survey analysis, this study concluded that while aspects of habituation were universally understood, habituation in its entirety was not. The quantitative analysis examined trends in mean time-on-task using number of visits as a covariate. Subjects repeatedly (20 captures per visit and 25 maximum attempts per visit) interacted with an iris recognition camera, returning for at least eight visits. The trends in the resulting time-on-task, image quality and matching performance indicated that habituation effects were identifiable near the end of the 2012 collection