A. Nait-Ali

Université Paris-Est Créteil Val de Marne - Université Paris 12, Créteil, Île-de-France, France

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Publications (62)6.44 Total impact

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    ABSTRACT: In this paper, we are interested in studying the robustness against noise of the biometric system based on Hand X-Ray images. Specifically, PSNR (Peak Signal to Noise Ratio) has been used to measure the distortion rate related to the acquisition conditions such as JPG compression, change in resolution and dose reduction. The identification rate has also been evaluated versus PSNR and image resolution. Index Terms— Fourier Transform, Human Identification, PSNR, Spoofing.
    The 20th LAAS International Science Conference Advanced Research for Better Tomorrow, 2014; 03/2014
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    ABSTRACT: In this paper, a new gender classification method based on x-ray images of hand is developed. The main idea aims at examining the effects of Phalanges features on gender classification. This method is based on the average width and the length of the fingers skeleton. Encouraging results have been obtained. Index Terms— Forensic Anthropology, Gender Classification, Phalanx Segmentation, Support Vector Machines.
    The 20th LAAS International Science Conference Advanced Research for Better Tomorrow, 2014; 03/2014
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    ABSTRACT: JPEG2000 is known as an efficient standard to encode images. However, at very low bit-rates, artifacts or distortions can be observed in decoded images. In order to improve the visual quality of decoded images and make them perceptually acceptable, we propose in this work a new preprocessing scheme. This scheme consists in preprocessing the image to be encoded using a nonlinear filtering, considered as a prior phase to JPEG 2000 compression. More specifically, the input image is decomposed into low- and high-frequency sub-images using morphological filtering. Afterward, each sub-image is compressed using JPEG2000, by assigning different bit-rates to each sub-image. To evaluate the quality of the reconstructed image, two different metrics have been used, namely (a) peak signal to noise ratio, to evaluate the visual quality of the low-frequency sub-image, and (b) structural similarity index measure, to evaluate the visual quality of the high-frequency sub-image. Based on the reconstructed images, experimental results show that, at low bit-rates, the proposed scheme provides better visual quality compared to a direct use of JPEG2000 (excluding any preprocessing).
    Signal Image and Video Processing 01/2014; · 0.41 Impact Factor
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    E. Zeybek, R. Fournier, A. Nait-ali
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    ABSTRACT: This paper presents a new method to segment bone tissue in an x-ray images. The proposed method is completely automatic. First of all, it enhances the contrast of the grayscale image using contrast-limited adaptive histogram equalization. Afterwards, the image intensity values are further modified by removing the background and soft tissue. Then a series of morphological operators, a opening-by-reconstruction followed by a closing-by-reconstruction, are applied to enhance the image by defining foreground objects and clean up the image. Finally holes are filled to preserve the bone structure. Keywords—X-Ray Images, Segmentation, CLAHE, Morphological Operations.
    2nd International Conference on Advances in Biomedical Engineering 2013; 09/2013
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    ABSTRACT: Abstract— In this work we propose a fully automatic algorithm for human identification using hand X-ray images. More specifically, this approach is appropriate to prevent forgeries in high security level systems. The proposed algorithm consists of three steps, namely: (1) segmentation of phalanges, (2) feature extraction using complex Fourier descriptors, (3) identification based on k-nearest neighbor method. To evaluate the proposed protocol, we have constructed a database containing 32 hand X-ray images, acquired using Apollo EZ Xray machine from 16 non-pathological adult individuals. Preliminary results show that a 100% identification rate is obtained in some specific conditions. Keywords— Hidden Biometrics, Hand X-ray, Segmentation, Fourier Transform, Human Identification, Spoofing, Forgeries.
    09/2013;
  • International Workshop on Systems, Signal Processing and their Applications, Algeria; 05/2013
  • Régis Fournier, A. Nait-ali
    Ref. No: 1353909, Year: 04/2013
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    ABSTRACT: This paper presents a discrete generalized multi-directional Radon transform (GMDRT)1 and its exact inversion algorithm. GMDRT is an extension of the classical Radon transform. It aims to project parameterized curves and geometric objects following several directions. For this purpose, we propose an algebraic formalism of the Radon Transform presenting the forward transform as a matrix-vector_ multiplication. We show in this paper that the exact inversion of the GMDRT exists. This property allows useful applications, in the field of digital image processing.
    Signal Processing 01/2013; 93(1):345-355. · 1.85 Impact Factor
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    ABSTRACT: In this paper, we propose to accurately detect from an image curvilinear features that can be approximated by polynomial curves. Having the a priori knowledge of a polynomial parameters (coefficients and degree), we give the possibility to recognize both the orientation and the position of the polynomial (if it exists) in the given image. For this objective, we present a new approach titled ”The Finite Polynomial Discrete Radon Transform” (FPDRT) that maps the initial image into a Radon space where each point presents the amount of evidence of the existence of a polynomial at the same position. The FPDRT sums the pixels centered on a polynomial and stores the result at the corresponding position in the Radon space. The FPDRT extends the formalism of the Finite Discrete Radon Transform(FRT) which is restricted to project the image along straight lines of equation y = mx + t where m and t are integers. Our method generalizes FRT by projecting the image with respect to polynomials of equation y = mx n + t where m, n and t are integers. The FPDRT method is exactly invertible, requires only arithmetic operations and is applicable to p×p sized images where p is a prime number. Several applications are allowable by the FPDRT such as fingerprint, palm print biometric applications and multi directional roads recognition.
    Lecture Notes in Computer Science 01/2013; 8157:249-258.
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    Journal of Basic and Applied Physics. 01/2013;
  • International Journal of Image, Graphics and Signal Processing. 01/2013;
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    International Journal of Signal and Image Processing. 01/2013;
  • Régis Fournier, A. Nait-Ali
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    ABSTRACT: L'analyse à diverses échelles de phénomènes complexes très irréguliers est une préoccupation quotidienne de chercheurs, d'ingénieurs et de praticiens de diverses disciplines (multimédia, télécommunications, médecine et biologie, traitement du signal et de l'image, mécanique des ruptures et des fluides, thermique, énergétique, microélectronique, astrophysique, finance, etc.). Le concept d'analyse multirésolution à base d'ondelettes constitue un outil universel performant répondant, souvent sans connaissance a priori, à ce besoin. Cet ouvrage revisite de façon simple et didactique les principales notions de l'analyse multirésolution à une et à deux dimensions et illustre l'intérêt de ce concept par quelques applications récentes en extraction de caractéristiques et classification, en compression adaptative, en masquage des erreurs de codage et de transmission d'images, en suppression de bruit corrélé, dont les plus remarquables relèvent du domaine médical (ECG, EEG, BCI, fMRI, détection de microemboles) et du domaine des télécommunications et multimédia (notamment en compression multimodale d'images HD).
    11/2012: pages 326; , ISBN: 978-2746223943
  • Qatar Foundation Annual Research Forum, Qatar; 10/2012
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    ABSTRACT: This paper presents a new variant of multimodal compression scheme based on a spiral insertion function in the wavelet domain. The main idea consists of inserting a decomposed signal into a decomposed image prior to a joint SPIHT compression process. The insertion phase is achieved in the detail sub-bands of the wavelet decomposition. The evaluation is assessed on both natural and medical images using objective and subjective comparison criteria. The experimental results showed the effectiveness of the proposed approach to obtain significant gains in terms of reconstructed signal (PRD %) and image (PSNR).
    11th International Conference on Information Sciences, Signal Processing and their Applications, Montreal, Quebec, Canada; 07/2012
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    International Conference on Information Science and Digital Content Technology, Jeju Island, Republic of Korea; 06/2012
  • International Conference on Informatics & Applications, Kuala Terengganu, Malaysia; 06/2012
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    ABSTRACT: The electrocardiogram (ECG) is an emerging novel biometric for human identification. It can be combined in a multi-modal biometric identification system or used alone for authentication of subjects. His primary application can be in health care systems where the ECG is used for health measurements. It does furthermore, better than any other biometrics measures, deliver the proof of subject’s being alive as extra information which other biometrics cannot deliver as easily. The main purpose of this study is to present a novel personal authentication approach for human authentication based on their ECG signals. We present a methodology for identity verification that quantifies the minimum number of heartbeats required to authenticate an enrolled individual. The cardiac signals were used to identify a total of 80 individuals obtained from four ECG databases from the Physionet database (MIT-BIH, ST-T, NSR, PTB) and an ECG database collected from 20 student volunteers from Paris Est University. Feature extraction was performed by using Discrete Wavelet Transform (DWT). Wavelets have proved particularly effective for extracting discriminative features in ECG signal classification. The Random Forest was then presented for the ECG signals authentication. Preliminary experimental results indicate that the system is accurate and can achieve a low false negative rate, low false positive rate and a 100% subject recognition rate for healthy subjects with the reduced set of features.
    International Journal on Cryptography and Information Security. 06/2012; 2(2).
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    International Journal on Computer Science and Engineering. 06/2012; 04(6):974-881.