In recent decades, we have witnessed the evolution of biometric technology from the first pioneering works in face and voice recognition to the current state of development wherein a wide spectrum of highly accurate systems may be found, ranging from largely deployed modalities, such as fingerprint, face, or iris, to more marginal ones, such as signature or hand. This path of technological evolution has naturally led to a critical issue that has only started to be addressed recently: the resistance of this rapidly emerging technology to external attacks and, in particular, to spoofing. Spoofing, referred to by the term presentation attack in current standards, is a purely biometric vulnerability that is not shared with other IT security solutions. It refers to the ability to fool a biometric system into recognizing an illegitimate user as a genuine one by means of presenting a synthetic forged version of the original biometric trait to the sensor. The entire biometric community, including researchers, developers, standardizing bodies, and vendors, has thrown itself into the challenging task of proposing and developing efficient protection methods against this threat. The goal of this paper is to provide a comprehensive overview on the work that has been carried out over the last decade in the emerging field of antispoofing, with special attention to the mature and largely deployed face modality. The work covers theories, methodologies, state-of-the-art techniques, and evaluation databases and also aims at providing an outlook into the future of this very active field of research.

Biometric Antispoofing Methods: A Survey in Face Recognition

A recent survey of iris biometric research from its inception through 2007, roughly 15 years of research, lists approximately 180 publications. This new survey is intended to update the previous one, and covers iris biometrics research over the period of roughly 2008–2010. Research in iris biometrics has expanded so much that, although covering only 3 years and intentionally being selective about coverage, this new survey lists a larger number of references than the inception-through-2007 survey.

https://www.springer.com/cda/content/document/cda_downloaddocument/9781447144014-c1.pdf?SGWID=0-0-45-1366206-p174543831

A Survey of Iris Biometrics Research: 2008–2010

In order to overcome the difficulty of password management and improve the usability of authentication systems, biometric authentication has been widely studied and has attracted special attention in both academia and industry. Many biometric authentication systems have been researched and developed, especially for mobile devices. However, the existing biometric authentication systems still have defects. Some biological features have not been deeply investigated. The existing systems could be vulnerable to attacks, such as replay attack and suffer from user privacy intrusion, which seriously hinder their wide acceptance by end users. The literature still lacks a thorough review on the recent advances of biometric authentication for the purpose of secure and privacy-preserving identification. In this paper, we classify and thoroughly review the existing biometric authentication systems by focusing on the security and privacy solutions. We analyze the threats of biometric authentication and propose a number of criteria with regard to secure and privacy-preserving authentication. We further review the existing works of biometric authentication by analyzing their differences and summarizing the advantages and disadvantages of each based on the proposed criteria. In particular, we discuss the problems of aliveness detection and privacy protection in biometric authentication. Based on our survey, we figure out a number of open research issues and further specify a number of significant research directions that are worth special efforts in future research.

/pdf/a-survey-on-biometric-authentication-toward-secure-and-27c7k9ql9p.pdf

A Survey on Biometric Authentication: Toward Secure and Privacy-Preserving Identification

This paper presents an online highly accurate system for automatic number plate recognition (ANPR) that can be used as a basis for many real-world ITS applications. The system is designed to deal with unclear vehicle plates, variations in weather and lighting conditions, different traffic situations, and high-speed vehicles. This paper addresses various issues by presenting proper hardware platforms along with real-time, robust, and innovative algorithms. We have collected huge and highly inclusive data sets of Persian license plates for evaluations, comparisons, and improvement of various involved algorithms. The data sets include images that were captured from crossroads, streets, and highways, in day and night, various weather conditions, and different plate clarities. Over these data sets, our system achieves 98.7%, 99.2%, and 97.6% accuracies for plate detection, character segmentation, and plate recognition, respectively. The false alarm rate in plate detection is less than 0.5%. The overall accuracy on the dirty plates portion of our data sets is 91.4%. Our ANPR system has been installed in several locations and has been tested extensively for more than a year. The proposed algorithms for each part of the system are highly robust to lighting changes, size variations, plate clarity, and plate skewness. The system is also independent of the number of plates in captured images. This system has been also tested on three other Iranian data sets and has achieved 100% accuracy in both detection and recognition parts. To show that our ANPR is not language dependent, we have tested our system on available English plates data set and achieved 97% overall accuracy.

Accurate Detection and Recognition of Dirty Vehicle Plate Numbers for High-Speed Applications

This paper considers three issues that arise in creating an algorithm for the robust detection of textured contact lenses in iris recognition images. The first issue is whether the accurate segmentation of the iris region is required in order to achieve the accurate detection of textured contact lenses. Our experimental results suggest that accurate iris segmentation is not required. The second issue is whether an algorithm trained on the images acquired from one sensor will well generalize to the images acquired from a different sensor. Our results suggest that using a novel iris sensor can significantly degrade the correct classification rate of a detection algorithm trained with the images from a different sensor. The third issue is how well a detector generalizes to a brand of textured contact lenses, not seen in the training data. This paper shows that a novel textured lens type may have a significant impact on the performance of textured lens detection.

Robust Detection of Textured Contact Lenses in Iris Recognition Using BSIF

In iris recognition system, accurate iris segmentation and localisation from eye image is the foremost important step. Success rate of any feature extraction algorithm of iris recognition systems is primarily decides by the performance of iris segmentation from an eye image. In the proposed method, the outer boundary of iris is calculated by tracing objects of various shape and structure. For inner iris boundary, two eye images of same subject at different intensities are compared with each other to detect the variation in pupil size. The variation in pupil size is also used for aliveness detection of iris. Thus, this approach is a very promising technique in making iris recognition systems more robust against fake-iris-based spoofing attempts. The algorithm is tested on Phoenix database of 384 images both eyes of 64 subjects. The success rate of accurate iris localisation from eye image is 99.48% with minimal loss of iris texture features in spatial domain as compared to all existing techniques. The processing time required is also comparable with existing techniques.

/pdf/dynamic-iris-localisation-a-novel-approach-suitable-for-fake-1q9vazruh8.pdf

Dynamic iris localisation: A novel approach suitable for fake iris detection

In this paper, authors have proposed a novel approach of  feature extraction of iris images using combination of  2D Dual Tree Rotated Complex Wavelet Transform (RCWT) and 2D Dual Trace Complex Wavelet Transform(CWT). This method provides features in 12 directions against 3 and 6 directions in DWT and CWT respectively. Iris features are obtained by computing  energies and standard deviation of detailed coefficients in 12 directions per stage, at 3 levels of decomposition. Canberra distance is used for matching. The results are obtained using DWT, CWT combination of CWT and RCWT on UBIRIS database of 2400 images. The performance measure, ZeroFAR, is reduced from 6.3 using DWT to 2.7 using proposed method. The method is also computationally efficient as compared to Gabor Filters.

Shift Invariant Iris Feature Extraction Using Rotated Complex Wavelet and Complex Wavelet for Iris Recognition System

This paper presents a new method for vehicle license plate localization. The proposed method uses wavelet decomposition for localizing the license plate. We first preprocess the image by masking the non-license plate border with the prior knowledge of the distance of the vehicle. We then use the unique property of sudden and a frequent transition which takes place across characters of the license plate to convert it to a license plate location detectable image by dividing the rows into its component zones. The component zone set which includes the license plate is determined using a transition counter and the zone which holds the maximum value is determined and validated using the wavelet based method. Simulation results are included to show the effectiveness of the proposed method for the localization of Indian license plates.

Vehicle license plate localization using wavelets

Dynamic iris localisation: a novel approach suitable for fake iris detection

The book presents three most significant areas in Biometrics and Pattern Recognition. A step-by-step approach for design and implementation of Dual Tree Complex Wavelet Transform (DTCWT) plus Rotated Complex Wavelet Filters (RCWF) is discussed in detail. In addition to the above, the book provides detailed analysis of iris images and two methods of iris segmentation. It also discusses simplified study of some subspace-based methods and distance measures for iris recognition backed by empirical studies and statistical success verifications.

Rajesh M. Bodade

Papers

Dynamic iris localisation: A novel approach suitable for fake iris detection

Shift Invariant Iris Feature Extraction Using Rotated Complex Wavelet and Complex Wavelet for Iris Recognition System

Vehicle license plate localization using wavelets

Dynamic iris localisation: a novel approach suitable for fake iris detection

Iris Analysis for Biometric Recognition Systems