Khalifa Djemal

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Various visual characteristics based discriminative classification has become a standard technique for image recognition tasks in heterogeneous databases. Nevertheless, the encountered problem is the choice of the most relevant features depending on the considered image database content. In this aim, feature selection methods are used to remove the effect(More)
Noise reduction is a very important task in image processing. In this aim, many approaches and methods have been developed and proposed in the literature. In this paper, we present a new restoration method for noisy images by minimizing the Total Variation (TV) under constraints using a multilayer neural network (MLP). Indeed, the obtained Euler-Lagrange(More)
In this paper a new soft subspace clustering algorithm is proposed. It is an iterative algorithm based on the minimization of a new objective function. The classification approach is developed by acting at three essential points. The first one is related to an initialization step; we suggest to use a multi-class support vector machine (SVM) for improving(More)
  • Khalifa Djemal
  • IEEE International Conference on Image Processing…
  • 2005
To limit the noise in an image, some techniques are based on the calculation of an average intensity in each pixel of the image by considering a some neighbor. However, these techniques tend to attenuate contours present in the image. This affect edge and particularly penalizing for the segmentation algorithms whose finality is to find contours. The(More)
In this paper we present a new algorithm to track an organ in a sequence of medical images in order to achieve a 3D reconstruction. The automatic method that we propose allows the tracking of the external contour of the anatomical organ in all the sequence from one contour initialized by the user on the first image. The required operations for our tracking(More)
In this paper, an heterogeneous image recognition system based on content description and classification is proposed. In this system and for an heterogeneous image database several features extraction methods are used and applied to better describes the images content. The features relevance is tested and improved through support vectors machines (SVMs)(More)
Many pattern recognition and machine learning methods have been used in cancer diagnosis. The Artificial Immune System (AIS) is a novel computational intelligence technique. Designed by the principles of the natural immune system, it is able of learning, memorize and perform pattern recognition. The AIS’s are used in various domains as intrusion detection,(More)