International Conference Papers

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Subject: search.filters.subject.Image segmentation

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    Object Detection in Images Based on Homogeneous Region Segmentation
    (Springer, 2018) Amrane, Abdesalam; Meziane, Abdelkrim; Boulkrinat, Nour El Houda
    Image segmentation for object detection is one of the most fundamental problems in computer vision, especially in object-region extraction task. Most popular approaches in the segmentation/object detection tasks use sliding-window or super-pixel labeling methods. The first method suffers from the number of window proposals, whereas the second suffers from the over-segmentation problem. To overcome these limitations, we present two strategies: the first one is a fast algorithm based on the region growing method for segmenting images into homogeneous regions. In the second one, we present a new technique for similar region merging, based on a three similarity measures, and computed using the region adjacency matrix. All of these methods are evaluated and compared to other state-of-the-art approaches that were applied on the Berkeley image database. The experimentations yielded promising results and would be used for future directions in our work.
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    Genetic algorithms and multifractal segmentation of cervical cell images
    (IEEE, 2003-07) Lassouaoui, Nadia; Hamami, Latifa
    This paper deals with the segmentation problem of cervical cell images. Knowing that the malignity criteria appear on the morphology of the core and the cytoplasm of each cell, then, the goal of this segmentation is to separate each cell on its component, that permits to analyze separately their morphology (size and shape) in the recognition step, for deducing decision about the malignity of each cell. For that, we use a multifractal algorithm based on the computation of the singularity exponent on each point of the image. For increasing the quality of the segmentation, we propose to add an optimization step based on genetic algorithms. The proposed processing has been tested on several images. Herein, we present some results obtained by two cervical cell images.