New online signature acquisition system

International audienceWe present a nonconstraining and low-cost online signature acquisition system that has been developed to enhance the performances of an existing multimodal biometric authentication system (based initially on both voice and image modalities). A laboratory prototype has been developed and validated for an online signature acquisition

Efficient Real Time Face Tracking Operator Study and Implementation within Virtex FPGA Technology

International audienceIn this paper, we present the development of a new real time face-tracking operator. This last is based on motion detection techniques, less complex than techniques based on skin color, which are sensitive to illumination or those based on geometric standards which are efficient but expensive in computation tasks. The developed operator allows a robust face tracking with a considerable reduction in hardware resources, more particularly memory resources, which remains a powerful criterion in the construction of real time embedded systems. Moreover, the operator maps efficiently into a highly pipelined architecture, well suited for an implementation in reconfigurable technology. The developed operator is implemented on a Virtex FPGA architecture. The obtained experimental results show the effectiveness and correctness of our approach

Tatouage topologique des images numériques

National audienceDans ce travail nous présentons une nouvelle approche pour le tatouage des images numériques basée sur la topologie des coupes. La technique proposée permet d'incruster une ou plusieurs marques dans une ou plusieurs parties de l'image localisées par un claque topologique contenant les composants connexes d'une coupe choisie. Le schéma de tatouage utilisé est spatial, additif et à clef secrète. Les expérimentations réalisées sur une base d'images importante montrent l'efficacité et la robustesse de la technique proposée

Real Time Embedded Moving Objects Detector - Study and Implementation Within Virtex FPGA Technology

This article details the design and the implementation of an efficient real time moving objects detector in the field of view of a fixed camera. The developed algorithm allows a robust motion detection and a considerable reduction in hardware resources, more particularly memory resources, which remains a powerful criterion in the construction of real time embedded systems. Moreover, the algorithm maps efficiently into a highly pipelined architecture, well suited to an implementation in reconfigurable technology. The algorithm is implemented on a Virtex FPGA architecture and operates in real time on video in CCIR format. The obtained experimental results show the effectiveness and correctness of our approach

Efficient online signature authentication approach

International audienceSignature authentication systems often have to focus their processing on acquired dynamic and/or static signatures descriptors to authenticate persons. This approach gives satisfactory results in ordinary cases but remains vulnerable against skilled forgeries. This is mainly because there is no relation between the signatory and his signature. We will show that the inclusion of the hand shape in the authentication process will considerably reduce the false acceptance rates of skilled forgeries and improve the authentication accuracy performances. A new online hand signature authentication approach based on both signature and hand shape descriptor is proposed. The signature acquisition is completely transparent, which allows a high level of security against fraudulent imitation attempts. Authentication performances are evaluated with extensive experiments. The obtained test results [equal  error  rate  (EER)=2%, genuine  acceptance  rate (GAR)=96%]confirm the efficiency of the proposed approach

A Multi-Modal Recognition System Using Face and Speech

International audienceNowadays Person Recognition has got more and more interest especially for security reasons. The recognition performed by a biometric system using a single modality tends to be less performing due to sensor data, restricted degrees of freedom and unacceptable error rates. To alleviate some of these problems we use multimodal biometric systems which provide better recognition results. By combining different modalities, such us speech, face, fingerprint, etc., we increase the performance of recognition systems. In this paper, we study the fusion of speech and face in a recognition system for taking a final decision (i.e., accept or reject identity claim). We evaluate the performance of each system differently then we fuse the results and compare the performances

Mutual Information Based Feature Selection for Fingerprint Identification

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Weakly supervised learning from scale invariant feature transform keypoints: an approach combining fast eigendecompostion, regularization, and diffusion on graphs

International audienceWe propose a unified approach to propagate knowledge into a high-dimensional space from a small informative set, in this case, scale invariant feature transform (SIFT) features. Our contribution lies in three aspects. First, we propose a spectral graph embedding of the SIFT points for dimensionality reduction, which provides efficient keypoints transcription into a Euclidean manifold. We use iterative deflation to speed up the eigendecomposition of the underlying Laplacian matrix of the embedded graph. Then, we describe a variational framework for manifold denoising based on p -Laplacian to enhance keypoints classification, thereby lessening the negative impact of outliers onto our variational shape framework and achieving higher classification accuracy through agglomerative categorization. Finally, we describe our algorithm for multilabel diffusion on graph. Theoretical analysis of the algorithm is developed along with the corresponding connections with other methods. Tests have been conducted on a collection of images from the Berkeley database. Performance evaluation results show that our framework allows us to efficiently propagate the prior knowledge