Sheikh Ziauddin

Iris recognition performance enhancement using weighted majority voting

Biometric authentication is a convenient and increasingly reliable way to prove ones identity. Iris scanning in particular is among the most accurate biometric authentication technologies currently available. However, despite their extremely high accuracy under ideal imaging conditions, existing iris recognition methods degrade when the iris images are noisy or the enrollment and verification imaging conditions are substantially different. To address this issue and enable iris recognition on less-than-ideal images, we introduce a weighted majority voting technique applicable to any biometric authentication system using bitwise comparison of enrollment-time and verification-time biometric templates. In a series of experiments with the CASIA iris database, we find that the method outperforms existing majority voting and reliable bit selection techniques. Our method is a simple and efficient means to improve upon the accuracy of existing iris recognition systems.

A robust hybrid iris localization technique

In this paper, a new iris localization method is presented. An iris recognition system acquires a human eye image, segments the iris region from the rest of the image, normalizes this segmented image and encodes features to get a compact iris template. Performance of all subsequent stages in an iris recognition system is highly dependent on correct detection of pupil-iris and iris-sclera boundaries in the eye images. In this paper, we present one such system which finds pupil boundary using image gray levels but uses edge detection and circular Hough transform to locate iris boundary. We introduce a number of optimizations to traditional Hough transform based methods. Experimental evaluation shows that the proposed system is accurate and efficient enough for real life applications.

An Image-Based CAPTCHA Scheme Exploiting Human Appearance Characteristics

CAPTCHAs are automated tests that are there to avoid misuse of computing and information resources by bots. Typical text-based CAPTCHAs are proven to be vulnerable against malicious automated programs. In this paper, we present an image-based CAPTCHA scheme using easily identifiable human appearance characteristics that overcomes the weaknesses of current text-based schemes. We propose and evaluate two applications for our scheme involving 25 participants. Both applications use same characteristics but different classes against those characteristics. Application 1 is optimized for security while application 2 is optimized for usability. Experimental evaluation shows promising results having 83% human success rate with Application 2 as compared to 62% with Application 1.

Robust iris verification for key management

In this paper, we present a method for secret key generation and recovery based on iris verification that, unlike typical systems which store iris templates persistently, stores recovery information on a smart card carried by the user. The scheme uses error-correcting codes to overcome the noisiness inherent in biometric readings. Our iris template incorporates reliable region selection, reliable bit estimation and one-sided masking techniques that provide for both robust verification and large key sizes. An implementation and experiments with the University of Bath iris dataset indicate that our scheme provides for generation and recovery of 260-bit keys with an EER of 0%.

A Two-Factor Mutual Authentication Scheme Using Biometrics and Smart Card

We present a remote authentication scheme that uses biometrics and smart card for its working. The security of our scheme relies on onewayness and collision-resistance of hash functions. We use error control codes to remove noise from biometric readings taken at different times. We provide a detailed security analysis and show that the proposed scheme is able to withstand many commonly known attacks against remote authentication schemes. In addition, the scheme does not store biometric templates on the server and provides mutual authentication between the user and the server.

An Efficient Scheme for Intra Prediction Block Size and Mode Selection in Advanced Video Coding

In H.264/MPEG-4 Advanced Video Coding (AVC) variable block-sized intra prediction modes are used in intra and inter frame coding to improve coding efficiency. In order to achieve best prediction mode a robust rate-distortion optimization (RDO) technique is employed for each macroblock (MB). The use of RDO process drastically increases the computational complexity of the encoder because of the large combinations of coding modes. This paper presents an efficient scheme based on spatial homogeneity measures to decide appropriate block size for intra prediction and to exclude as many intra prediction modes as possible prior to the RDO process. Experimental results show that the proposed scheme speeds up the encoding process by 69% without significant degradation in video quality.

Cryptanalysis and Improvement of a Two-Factor User Authentication Scheme Providing Mutual Authentication and Key Agreement over Insecure Channels

Abstract — A two-factor remote authentication scheme was presented by Chun-Ta Li et al. in 2010. We present the framework of an impersonation attack against their scheme if the smart card gets stolen. We show that it is easy for an attacker to compute password of a user by using information extracted from the stolen smart card. We also propose a simple and easy solution to fix this problem. Index Terms — Authentication schemes, cryptanalysis, mutual authentication, smart card. I. I NTRODUCTION To avoid unauthorized access, some security mechanism is needed to authenticate legitimate users. There are three common ways to authenticate a user: what you know (a pin or a password), what you have (a hardware token) and what you are (a biometric trait). The most commonly used mechanism for authentication is password. As it is not easy to remember strong passwords especially when a user has multiple accounts, this leads to either using same password for all accounts or selecting passwords with low entropy that can easily be guessed. Hardware token-based schemes are also vulnerable because the hardware token can be lost, stolen, forged or compromised. Biometric-based authentication schemes are resistive for most of the problems in token-based and password systems and provide better security then the other two techniques, yet these are not widely adopted mainly because they are expensive to implement and use. Due to the above-mentioned problems with the individual authentication techniques, researchers have proposed to use two-factor authentication where, in most cases, the two factors being used are a password and a hardware token typically a smart card. Using two-factors increases both security and reliability of the overall system. In this paper, we have analyzed one of the two factor authentication schemes proposed by Chun-Ta Li

Interactive Slide Navigation: An Approach for Manipulating Slides with Augmented Reality Markers

The use of PowerPoint slides is an interactive way of communication in a classroom environment. To make it more effective, different techniques for the manipulation, annotation, and navigation of slides have been utilized. We presented the use of Augmented Reality technology to manipulate, annotate and navigate through PowerPoint slides. We used Augmented Reality marker recognition techniques by employing an Augmented Reality ToolKit. We performed tests by analyzing Augmented Reality marker IDs and their translational and rotational gestures. We used 1) simple flat Augmented Reality markers, 2) finger Augmented Reality markers, 3) cube markers, 4) illuminated markers, and 5) retro-reflective markers to manipulate slides. The results indicate that finger Augmented Reality markers are easy to handle and perform better than other types of markers. Cube markers are especially helpful in performing rotational gestures, while illuminated and retro-reflective markers provide moderate results in comparison with simple flat markers. As far as we know, we are the first to use Augmented Reality technology for handling slides and providing the presenter with distant access to the presentation.

A hybrid scheme based on pipelining and multitasking in mobile application processors for advanced video coding

One of the key requirements for mobile devices is to provide high-performance computing at lower power consumption. The processors used in these devices provide specific hardware resources to handle computationally intensive video processing and interactive graphical applications. Moreover, processors designed for low-power applications may introduce limitations on the availability and usage of resources, which present additional challenges to the system designers. Owing to the specific design of the JZ47x series of mobile application processors, a hybrid software-hardware implementation scheme for H.264/AVC encoder is proposed in this work. The proposed scheme distributes the encoding tasks among hardware and software modules. A series of optimization techniques are developed to speed up the memory access and data transferring among memories. Moreover, an efficient data reusage design is proposed for the deblock filter video processing unit to reduce the memory accesses. Furthermore, fine grained macroblock (MB) level parallelism is effectively exploited and a pipelined approach is proposed for efficient utilization of hardware processing cores. Finally, based on parallelism in the proposed design, encoding tasks are distributed between two processing cores. Experiments show that the hybrid encoder is 12 times faster than a highly optimized sequential encoder due to proposed techniques.