Mahaman Sani Chaibou

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This paper presents a semantic image segmentation approach that combines a fuzzy region classification and a contextual region-growing. First image is over-segmented and a domain knowledge based fuzzy classification is applied on obtained regions to provide a fuzzy semantic labeling. This allows the proposed approach to operate at high level instead of(More)
We present in this paper an image segmentation approach that combines a fuzzy semantic region classification and a context based region-growing. Input image is first over-segmented. Then, prior domain knowledge is used to perform a fuzzy classification of these regions to provide a fuzzy semantic labeling. This allows the proposed approach to operate at(More)
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