Mounir Sayadi

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In this paper we propose a new knowledge model using the Dempster-Shafer’s evidence theory for image segmentation and fusion. The proposed method is composed essentially of two steps. First, mass distributions in Dempster-Shafer theory are obtained from the membership degrees of each pixel covering the three image components (R, G and B). Each membership’s(More)
Gabor filtering is a widely applied approach for texture analysis. This technique shows a strong dependence on certain number of parameters. Unfortunately, each variation of values of any parameter may affect the texture characterization performance. Moreover, Gabor filters are unable to extract micro-texture features which also have a negative effect on(More)
Automatic segmentation of stained breast tissue images helps pathologists to discover the cancer disease earlier. Separation of touching cells presents many difficulties to the traditional segmentation algorithms. In this paper, we propose a new automatic method to segment clustered cancer cells. In the first step, we detect cell regions using a modified(More)
A novel method of colour image segmentation based on fuzzy homogeneity and data fusion techniques is presented. The general idea of mass function estimation in the Dempster-Shafer evidence theory of the histogram is extended to the homogeneity domain. The fuzzy homogeneity vector is used to determine the fuzzy region in each primitive colour, whereas, the(More)
Segmentation is the main sensitive problem in the automatic image analysis of histopathology specimens. In the stained breast image tissue, cancer cells present a large variety in their characteristics that bring various difficulties for traditional segmentation algorithms. In this paper, we propose an automatic segmentation method for breast cancer cell(More)
In this paper, we present a combination between Empirical Mode Decomposition (EMD) approach and Hilbert transform approach for the purpose of R peak detection in Electrocardiogram (ECG) signal. This algorithm uses the EMD to find the signal which highlights the region of the QRS complex in ECG signal by combining the first three IMF that contain sufficient(More)
Automatic image segmentation of immunohistologically stained breast tissue sections helps pathologists to discover the cancer disease earlier. The detection of the real number of cancer nuclei in the image is a very tedious and time consuming task. Segmentation of cancer nuclei, especially touching nuclei, presents many difficulties to separate them by(More)