Omar Nibouche

Automatic Recognition of Shoeprints using Fourier-Mellin Transform

This paper proposes a technique for automatically recognising shoeprint images for use in forensic science. The method uses the Fourier-Mellin transform to produce translation, rotation and scale invariant features. A two dimensional correlation is employed as the similarity metric for the classification process. Experiments were conducted on a database of 500 different shoeprint images representing a part of available shoes on the market. In order to test the robustness of the method, test images including different perturbations such as noise addition and cropping (partial shoeprints) were generated. Experimental results show that the proposed method is very practical providing attractive performance when processing distorted shoeprint images.

Partial palmprint matching using invariant local minutiae descriptors

In forensic investigations, it is common for forensic investigators to obtain a photograph of evidence left at the scene of crimes to aid them catch the culprit(s). Although, fingerprints are the most popular evidence that can be used, scene of crime officers claim that more than 30% of the evidence recovered from crime scenes originate from palms. Usually, palmprints evidence left at crime scenes are partial since very rarely full palmprints are obtained. In particular, partial palmprints do not exhibit a structured shape and often do not contain a reference point that can be used for their alignment to achieve efficient matching. This makes conventional matching methods based on alignment andminutiae pairing, as used in fingerprint recognition, to fail in partial palmprint recognition problems. In this paper a new partial-to-full palmprint recognition based on invariant minutiae descriptors is proposedwhere the partial palmprints minutiae are extracted and considered as the distinctive and discriminating features for each palmprint image. This is achieved by assigning to eachminutiae a feature descriptor formed using the values of all the orientation histograms of the minutiae at hand. This allows for the descriptors to be rotation invariant and as such do not require any image alignment at the matching stage. The results obtained showthat the proposed technique yields a recognition rate of 99.2%. The solution does give a high confidence to the judicial jury in their deliberations and decision.

Rotation Invariant Matching of Partial Shoeprints

In this paper, we propose a solution for the problem of rotated partial shoeprint retrieval, based on the combined use of local points of interest and SIFT descriptor. Once the generated features are encoded using SIFT descriptor, matching is carried out using RANSAC to estimate a transformation model and establish the number of its inliers which is then multiplied by the sum of point-to-point Euclidean distances below a hard threshold. We demonstrate that such combination can overcome the issue of retrieval of partial prints in the presence of rotation and noise distortions. Conducted experiments have shown that the proposed solution achieves very good matching results and outperforms similar work in the literature both in terms of performance and complexity.

FPGA-Based Discrete Wavelet Transforms System

Although FPGA technology offers the potential of designing high performance systems at low cost, its programming model is prohibitively low level. To allow a novice signal/image processing end-user to benefit from this kind of devices, the level of design abstraction needs to be raised. This approach will help the application developer to focus on signal/image processing algorithms rather than on low-level designs and implementations. This paper presents a framework for an FPGA-based Discrete Wavelet Transform system. The approach helps the end-user to generate FPGA configurations for DWT at a high level without any knowledge of the low-level design styles and architectures.

An improved palmprint recognition system using iris features

This paper presents a bimodal biometric recognition system based on the extracted features of the human palmprint and iris using a new graph-based approach termed Fisher locality preserving projections (FLPP). This new technique employs two graphs with the first being used to characterize the within-class compactness and the second dedicated to the augmentation of the between-class separability. By applying the FLPP, only the most discriminant and stable palmprint and iris features are retained. FLPP was implemented on the frequency domain by transforming the extracted region of interest extraction of both biometric modalities using Fourier transform. Subsequently, the palmprint and iris features vectors obtained are matched with their counterpart in the templates databases and the obtained scores are fused to produce a final decision. The proposed combination of palmprint and iris patterns has shown an excellent performance compared to unimodal palmprint biometric recognition. The system was evaluated on a database of 108 subjects and the experimental results show that our system performs very well and achieves a high accuracy expressed by an equal error rate of 0.00%.

New architectures for serial-serial multiplication

Traditional serial-serial multiplier structures suffer from an inefficient generation of partial products, which leads to hardware overuse and slow speed systems. In this paper, two new architectures for fully serial multiplication are presented. To the best of our knowledge, the first structure is the first fully serial multiplier reported in the literature with comparable performance-in terms of speed-to existing serial-parallel multipliers. The second structure requires an extra multiplexer in the clock path thus making it slower, but has the merit of reducing the latency of the multiplier. Both structures are systolic and need near communication links only. Compared with available architectures, an FPGA based implementation has shown an increase in the speed of the multipliers by about 200% for the first structure and 150% for the second structure.

Partial shoeprint retrieval using multiple point-of-interest detectors and SIFT descriptors

Shoeprint evidence collected from crime scenes can play an important role in forensic investigations. Usually, the analysis of shoeprints is carried out manually and is based on human expertise and knowledge. As well as being error prone, such a manual process can also be time consuming; thus affecting the usability and suitability of shoeprint evidence in a court of law. Thus, an automatic system for classification and retrieval of shoeprints has the potential to be a valuable tool. This paper presents a solution for the automatic retrieval of shoeprints which is considerably more robust than existing solutions in the presence of geometric distortions such as scale, rotation and scale distortions. It addresses the issue of classifying partial shoeprints in the presence of rotation, scale and noise distortions and relies on the use of two local point-of-interest detectors whose matching scores are combined. In this work, multiscale Harris and Hessian detectors are used to select corners and blob-like structures in a scale-space representation for scale invariance, while Scale Invariant Feature Transform (SIFT) descriptor is employed to achieve rotation invariance. The proposed technique is based on combining the matching scores of the two detectors at the score level. Our evaluation has shown that it outperforms both detectors in most of our extended experiments when retrieving partial shoeprints with geometric distortions, and is clearly better than similar work published in the literature. We also demonstrate improved performance in the face of wear and tear. As matter of fact, whilst the proposed work outperforms similar algorithms in the literature, it is shown that achieving good retrieval performance is not constrained by acquiring a full print from a scene of crime as a partial print can still be used to attain comparable retrieval results to those of using the full print. This gives crime investigators more flexibility is choosing the parts of a print to search for in a database of footwear.

An FPGA-based wavelet transforms coprocessor

Although FPGA technology offers the potential of designing high performance systems at low cost for a wide range of applications, its programming model is prohibitively low level requiring either a dedicated FPGA-experienced programmer or basic digital design knowledge. To allow a signal/image processing end-user to benefit from this kind of device, the level of design abstraction needs to be raised, even beyond a hardware description language level (e.g. VHDL). This approach will help the application developer to focus on signal/image processing algorithms rather than on low-level designs and implementations. This paper aims to present a framework for an FPGA-based coprocessor dedicated to discrete wavelet transforms (DWT). The proposed approach will help the end-user to generate FPGA configurations for DWT at the highest level without any knowledge of the low-level design styles and architectures.

New iterative algorithms and architectures of modular multiplication for cryptography

Algorithms and architectures for performing modular multiplication operations, which is central to crypto-system and authentication schemes, are important in todays needs of secure communications. This paper presents two new iterative algorithms for modular multiplication. The implementation of these algorithms yields to scalable architectures that can be used for any modulus without altering the design. In addition, the Radix-2 algorithm shows almost similar features when compared with similar architectures available in the literature. Furthermore, the radix-4 algorithm can be used to develop higher radix algorithms since it only requires the use of powers of two of the modulus.

A new pipelined digit serial-parallel multiplier

Digit-serial architectures obtained using traditional unfolding and folding techniques cannot be pipelined beyond a certain level because of the presence of feedback loops. In this paper, a novel approach for the design of pipelined digit serial-parallel multipliers is presented.