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Auflistung nach Autor:in "Dorizzi, Bernadette"

1 - 4 von 4
  • Konferenzbeitrag
    How a local quality measure can help improving iris recognition
    (BIOSIG 2012, 2012) Cremer, Sandra; Dorizzi, Bernadette; Garcia-Salicetti, Sonia; Lempérière, Nadège
    The most common iris recognition systems extract features from the iris after segmentation and normalization steps. In this paper, we propose a new strategy to select the regions of normalized iris images that will be used for feature extraction. It consists in sorting different sub-images of the normalized images according to a GMM-based local quality measure we have elaborated and selecting the N best sub-images for feature extraction. The proportion of the initial image that is kept for feature extraction has been set in order to compromise between minimizing the amount of noise taken into account for feature extraction and maximizing the amount of information available for matching. By proceeding this way, we privilege the regions for which our quality measure gives the highest values, namely regions of the iris that are highly textured and free from occlusion, and minimize the risks of extracting features in occluded regions to which our quality measure gives the lowest values. We also control the amount of information we use for matching by including, if necessary, regions that are given intermediate values by our quality measure and are free from occlusion but barely textured. Experiments were performed on three different databases: ND-IRIS- 0405, Casia-IrisV3-Interval and Casia-IrisV3-Twins, and show a significant improvement of recognition performance when using our strategy to select regions for feature extraction instead of using a binary segmentation mask and considering all unmasked regions equally.
  • Konferenzbeitrag
    A novel crypto-biometric scheme for establishing secure communication sessions between two clients
    (BIOSIG 2012, 2012) Kanade, Sanjay G.; Petrovska-Delacrétaz, Dijana; Dorizzi, Bernadette
    Biometrics and cryptography are two tools which have high potential for providing information security and privacy. A combination of these two can eliminate their individual shortcomings, such as non-revocability, non-diversity, and privacy issues in biometrics and need of strong authentication in cryptography. Cryptobiometric systems combine techniques from biometrics and cryptography for these purposes, and more interestingly, to obtain biometrics based cryptographic keys. In this paper, we address the problem of sharing these keys. We propose a cryptobiometric scheme in which two clients can share a session key securely and establish a secure communication session. The scheme involves a Central Authority for Registration and Authentication (CARA) with which the clients are registered. The CARA stores biometric data only in transformed, cancelable form, allowing for easy revocation of the templates and protecting privacy. There are two distinctive features of this protocol (1) it achieves mutual authentication and starts secure communication between two clients which may be previously unknown to each other, and (2) this protocol works even if the two clients use different biometric modalities in the same (as well as in different) session.
  • Konferenzbeitrag
    Probabilistic matching pair selection for SURF-based person re-identification
    (BIOSIG 2012, 2012) Khedher, Mohamed Ibn; El-Yacoubi, Mounim A.; Dorizzi, Bernadette
    The objective of this paper is to study the performance of human reidentification based on multi-shot SURF and to assess its degradation according to the angular difference between the test and reference video scene view angles. In this context, we propose a new automatic statistical method of acceptance and rejection of SURF correspondence based on the likelihood ratio of two GMMs learned on the reference set and modeling the distribution of distances resulting from matching sequences associated with the same person and with different persons respectively. The experimental results show that our approach compares favorably with the state of the art and achieves a good performance.
  • Konferenzbeitrag
    Quality driven iris recognition improvement
    (BIOSIG 2013, 2013) Cremer, Sandra; Lemperiere, Nadege; Dorizzi, Bernadette; Garcia-Salicetti, Sonia
    The purpose of the work presented in this paper is to adapt the feature extraction and matching steps of iris recognition to the quality of the input images. To this end we define a GMM-based global quality metric associated to a pair of normalized iris images. It quantifies the amount of artifact in these images as well as the amount of texture in artifact-free regions. First we use this metric to adjust, for each pair of irises, the proportion of the normalized image selected on a local quality criteria for feature extraction. This approach is tested with two matching techniques: one performs a bit to bit comparison of binary feature vectors and the other one computes local cross-correlations between real valued vectors. We show that our approach is effective with both techniques. Then we use our metric to choose the matching technique that is best adapted to each image pair in order to make a good compromise between accuracy and speed.