Publications

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    ABSTRACT: Palmprint recognition, as a reliable personal identification method, has received an increasing attention and became an area of intense research during recent years. In this paper, we propose a generic biometric system that can be adopted with or without contact depending on the capturing system to ensure public security based on palmprint identification. This system is based on a new global approach that focuses only on areas of the image having the most discriminating features for recognition. The presented new approach was evaluated experimentally on two large databases, namely,“CASIA-Palmprint” and “PolyU-Palmprint”; the results of this evaluation show promising results and demonstrate the effectiveness of the proposed approach.
    Multimedia Tools and Applications 02/2014; · 1.01 Impact Factor
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    ABSTRACT: Lane detection and tracking are very crucial treatments in lane departure warning systems as they help the vehicle-mounted system to keep its lane. In this context, the authors' work aims to develop vision-based lane detection and tracking method to detect and track lane limits in highways and main roads. The authors' contribution focuses on the detection step. By exploiting the fact that, in an image, the road can be formed by linear and curvilinear portions, the authors propose two types of appropriate treatments to detect the lane limits. The authors' method offers high precision rates independently of the painted lane marking's characteristics, of the time of acquisition and in different weather conditions. Besides the challenges it overcomes, the authors' method has the advantage of operating with a timing complexity that is reasonable for real-time applications. As shown experimentally, compared to three leading methods from the literature, the authors' method has a higher efficiency.
    International Journal of Computer Vision and Image Processing. 07/2013; 3(3):1-15.
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    ABSTRACT: Hand detection is the first step of any hand biometric recognition process, which determines the outcome of the following treatments. In this paper, we propose a robust method for hand detection without contact and without constraints on the capture environment for hand biometric applications. This method is based on a color based approach adopting a non-parametric modeling. Our contribution consists mainly in the choice of the most relevant color axes and the choice of the decision rules automatically using a process of the data-mining as a new philosophy of data processing. To improve the achieved results of skin detection and to determine the hand region in the image, a succession of post-processing was proposed. Our hand detection method was evaluated experimentally on a real database; the outcomes of this evaluation show promising results and demonstrate the effectiveness of the proposed method.
    Computer Systems and Applications (AICCSA), 2013 ACS International Conference on; 01/2013
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    ABSTRACT: Hand detection is the first step of any hand biometric recognition process, which determines the outcome of the following treatments. In this study, the authors propose a robust method for hand detection without contact and without constraints on the capture environment. This method is based on a data-mining process for skin-colour modelling. The presented data-mining process offers several advantages like the choice of the most relevant colour axes and the automatic choice of the decision rules. To improve the achieved results of skin detection and to determine the hand region in the image, a succession of postprocessings was proposed. The authors hand detection method was evaluated experimentally on a real database, namely, `Sfax-Miracl hand database'; the outcomes of this evaluation show promising results and demonstrate the effectiveness of the proposed method.
    IET Image Processing 01/2013; 7(8):742-750. · 0.90 Impact Factor
  • H. Mliki, N. Fourati, S. Smaoui, M. Hammami
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    ABSTRACT: Over the last two decades, the advances in computer vision and pattern recognition power have opened the door to new opportunity of automatic facial expression recognition system. In this work, we have introduced a new feature-based approach for facial expressions recognition. The proposed approach provides full automatic solution to identify human expressions as well as overcoming facial expressions variation and intensity problems. Facial features component were automatically detected and segmented. Then, we have detected facial feature points which go with facial expression deformations. Afterwards, distances between these points were computed and used through Data mining technique to generate a set of relevant prediction rules able to classify facial expressions. We took into account the intensity of JOY expression. Thus, we have defined SMILE expression as the lowest intensity of JOY. Seven facial expression classes were defined: JOY, SMILE, SURPRISE, DISGUST, ANGER, SADNESS, and FEAR We have appraised experimental study to evaluate the performance of the proposed solution.
    Computer Systems and Applications (AICCSA), 2013 ACS International Conference on; 01/2013
  • Hazar Mliki, Mohamed Hammami, Hanêne Ben-Abdallah
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    ABSTRACT: This paper presents a new system to achieve face detection and tracking in video sequences. We have performed a combination between detection and tracking modules to overcome the different challenging problems that can occur while detecting or tracking faces. Our proposed system is composed of two modules: Face detection module and face tracking module. In the face detection module, we have used skin color and motion information to extract regions of interest and cut off false positive face. This filtering step has enhanced the next face tracking processing step, as it helps to avoid tracking false positive faces. Regarding tracking module, we have used face detection results to keep the face tracker updated. In order to carry on tracking face we have used particle filter technique which was adapted to track multiple faces. Moreover, each tracked face was described by a defined state: tracked, occluded, entered, left or stopped. The performance of our detect-track system was evaluated using several experiments. This evaluation proved the robustness of our face detection-track system as it supports automatic tracking with no need to manual initialization or re-initialization and reaches best performance to deal with different challenging problems.
    Proceedings of the 11th IFIP TC 8 international conference on Computer Information Systems and Industrial Management; 09/2012
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    ABSTRACT: In this paper, we present an algorithm for tracking objects in road traffic sequences which is based on coherent strategy. This strategy relies on two times processing. Firstly, a Short-Term Processing (STP) based on spatial analysis and multilevel region descriptors matching allows identification of objects interactions and particular objects states. Secondly, a Long- Term Processing (LTP) is applied to cope with track management issues. In fact LTP feedbacks objects and their corresponding regions in each frame to update tracked object attributes. In case of merging objects, attributes are obtained using Template matching. An experimental study by quantitative and qualitative evaluations shows that the proposed approach can deal with multiple rigid objects whose sizes vary over time. The obtained results prove that our method can provide an effective and stable road objects tracks.
    Proceedings of the 5th international conference on Image and Signal Processing; 06/2012
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    ABSTRACT: A new branch of biometrics, hand recognition, has attracted increasing amount of attention in recent years. In this paper, we propose an approach of hand detection based skin color pixel for biometric applications using multi layer perceptron (MLP) neural network. This later has the ability to classify skin pixels belonging to people with different skin tones and captured in different lighting conditions and complex background environments. To improve the achieved results, a succession of post-processing was proposed. The choice of the database is an important step in testing a biometric process. For this, we build a database named "Sfax-Miracl hand database". This database contains a total of 1080 images having the advantage of being captured from freely posed hands in contact free settings. Various conducted experiments on this database show promising results and demonstrate the effectiveness of the proposed approach.
    Proceedings of the 5th international conference on Image and Signal Processing; 06/2012
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    ABSTRACT: In this paper, we tackle the shadow problem in depth for a better foreground segmentation. We propose a novel variant of co-training technique for shadow detection and removal in uncontrolled scenes. This variant works according to a powerful temporal behavior. Setting co-training parameters is based on an extensive experimental study. The proposed co-training variant runs periodically to obtain more generic classifier, thus improving speed and classification accuracy. An experimental study by quantitative, qualitative and comparative evaluations shows that the proposed method can detect shadow robustly and remove the ‘cast' part accurately from videos recorded by a static camera and under several constraints.
    Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I; 06/2012
  • M. Hazar, H. Mohamed, B. Hanene
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    ABSTRACT: In this paper we deal with the problem of lowering down the difficulty of face detection in video. Most of the recently developed systems swap detection accuracy for higher speeds, or vice versa. We have proposed a robust approach which makes use of spatial and temporal information in video to reduce time execution and improve precision rate. Our experiments show that our proposed approach proves efficiency without sacrificing real-time performance which makes it well-suited for live video applications.
    Parallel and Distributed Processing with Applications (ISPA), 2012 IEEE 10th International Symposium on; 01/2012
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    ABSTRACT: Lane detection consists of detecting the lane limits where the vehicle carrying the camera is moving. The aim of this study is to propose a lane detection method through digital image processing. Morphological filtering, Hough transform and linear parabolic fitting are applied to realize this task. The results of our proposed method are compared with three proposed researches. The method presented here was tested on video sequences filmed by the authors on Tunisian roads, on a video sequence provided by Daimler AG as well as on the PETS2001 dataset provided by the Essex University. KeywordsDriver assistance system–Lane detection–Hough transform–Morphological filtering
    08/2011: pages 46-57;
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    ABSTRACT: The detection of moving objects is a basic task for computer vision system. The performances of these systems are not sufficient for many applications. One of the main reasons is that the moving objet detection task has many difficulties in dealing with various constraints like the variations of the environment. A great number of methods were already proposed. We classify contributions reported in the literature in four approaches with a categorization based on inter-frame processing they adopt methods based on Inter-Frame Difference (IFD), those based on Background Modeling (BM), methods based on the Optical Flow (OF), and hybrid methods. In this paper, we present our proposed methods to detect moving objects. The first is a hybrid method that combines the inter-images difference based on entropy image and optical flow computed by a local method with a hierarchical coarse-to-fine optical flow estimation. The second is an adaptive background modeling based on dynamic matrix and spatio-temporal analyses of scenes. A comparative study by quantitative evaluations shows that the proposed BM method can detects foreground robustly and accurately from videos recorded by a static camera and which include several constraints such as sudden and gradual illumination changes, shaking camera, background component changes, ghost, and foreground speed.
    Journal of Next Generation Information Technology. 04/2011; 2.
  • Salma Ben Jemaa, Mohamed Hammami
    VISAPP 2011 - Proceedings of the Sixth International Conference on Computer Vision Theory and Applications, Vilamoura, Algarve, Portugal, 5-7 March, 2011; 01/2011
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    ABSTRACT: Obstacle detection is an important component in driver assistance as it helps systems to locate obstacles and then to prevent collisions. The aim of this study is to develop an obstacle detection module through digital images processing. We present a hybrid stereo vision-based method that combines stereo matching and homographic transformation methods. We use a sparse matching method in order to get a rapid geometric representation of the road scene that allows us to extract the upper and lower parts of obstacles. According to the position of the lower part, our method uses either the dense stereo matching or the homographic transformation methods to extract the candidate obstacles regions. A verification test is performed to verify whether the retained region is an obstacle or not. In order to avoid collisions, we compute the distance to the preceding obstacle to maintain the vehicle carrying the camera at a safety distance. The method presented here was tested on DIPLODOC 1 road stereo sequence captured on a highway. The obtained results prove the efficiency of our proposed method.
    01/2011;
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    ABSTRACT: In this paper, we propose a new approach, called RoadGuard, for Highway Control and Management System. RoadGuard is based on counting and tracking moving vehicles robustly. Our system copes with some challenges related to such application processing steps like shadow, ghost and occlusion. A new algorithm is proposed to detect and remove cast shadow. The occlusion and ghost problems are resolved by the adopted tracking technique. A comparative study by quantitative evaluations shows that the proposed approach can detect vehicles robustly and accurately from highway videos recorded by a static camera which include several constraints. In fact, our system has the ability to control highway by detecting strange events that can happen like sudden stopped vehicles in roads, parked vehicles in emergency zones or even illegal conduct such going out from the road. Moreover, RoadGuard is capable to manage highways by saving information about date and time of overloaded roads
    VISAPP 2011 - Proceedings of the Sixth International Conference on Computer Vision Theory and Applications, Vilamoura, Algarve, Portugal, 5-7 March, 2011; 01/2011
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    ABSTRACT: In driver assistance systems, lane detection and tracking are very crucial treatments to locate the vehicle and to track its position on the road. The aim of this study is to propose lane detection and tracking method. The first step in this method detects road limits on the first acquired image. The detected limits would be the input for the second step, namely the "tracking step", which consists in providing a continuous detection of the limits in all frames by updating the previously detected limits. Lane departure is also analyzed for the lateral control of the vehicle. The approach presented here was tested on video sequences filmed by the authors on Tunisian roads, on a video sequence provided by Daimler AG as well as on the PETS2001 dataset provided by the Essex University.
    Knowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Kaiserslautern, Germany, September 12-14, 2011, Proceedings, Part I; 01/2011
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    ABSTRACT: The development of the Web has been paralleled by the proliferation of a harmful content on its pages. Using Violent Web images as a case study, we tend to present a novel approach to their classification. This subject is of high importance as it has a potential use in many applications such as violent Web sites filtering. We, therefore, focus our attention on the extraction of contextual image features from the Web page. Also, we present a comparative study of different data mining techniques to classify violent Web images. The results we achieved show that our approach can detect violent content effectively.
    Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), Sierre, Switzerland, March 22-26, 2010; 01/2010
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    ABSTRACT: Fast and accurate foreground detection in video sequences is the first step in many computer vision applications. In this paper, we propose a new method for background modeling that operates in color and gray spaces and that manages the entropy information to obtain the pixel state card. Our method is recursive and does not require a training period to handle various problems when classify pixels into either foreground or background. First, it starts by analyzing the pixel state card to build a dynamic matrix. This latter is used to selectively update background model. Secondly, our method eliminates noise and holes from the moving areas, removes uninteresting moving regions and refines the shape of foregrounds. A comparative study through quantitative and qualitative evaluations shows that our method can detect foreground efficiently and accurately in videos even in the presence of various problems including sudden and gradual illumination changes, shaking camera, background component changes, ghost, and foreground speed.
    International Conference on Digital Image Computing: Techniques and Applications, DICTA 2010, Sydney, Australia, 1-3 December, 2010; 01/2010
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    ABSTRACT: In this paper, we present a lane detection algorithm based on hough transform and linear parabolic fitting. The candidate pixels are collected after image contrast enhancement while using morphological filters. The algorithm was tested on image sequences we filmed on the roads of Tunisia and on images from the PETS2001 dataset provided by Essex University (England). These images present different environment conditions such as shadow, partial coverage of the markings by obstacles, different lane markings that can be blurred or well contrasted, and different weather conditions.
    Proceedings of the 2nd International Conference on Computer Science and its Applications, CSA 2009, December 10-12, 2009, Jeju Island, Korea; 01/2009
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    ABSTRACT: In this article, we present a contribution to the violent Web images classification. This subject is deeply important as it has a potential use for many applications such as violent Web sites filtering. We propose to combine the techniques of image analysis and data-mining to relate low level characteristics extracted from the image's colors to a higher characteristic of violence which could be contained in the image. We present a comparative study of different data mining techniques to classify violent Web images. Also, we discuss how the combination learning based methods can improve accuracy rate. Our results show that our approach can detect violent content effectively.
    Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Antonio, TX, USA, 11-14 October 2009; 01/2009

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