Fuzzy-connected 2D image segmentation

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In images, one of the most difficult tasks is their segmentation, which is a process of dividing the image into regions of interest, which permits to analyze the image more easily, and, additionally, these segments can be classified as object or non-object regions. Broadly, segmentation methods can be divided into three categories: edge-based, region-based, and model-based. The method performed in this paper is Fuzzy connectivity, which can be classified as a region-based method, in which the regions are obtained by pixel connectivity, and by using two criteria, fuzzy adjacency and fuzzy affinity. The first criterion is computed by considering the distance between 2 pixels and the second is computed by bearing in mind the similarity intensity measurement space.The fuzzy-connected segmentation method presents some advantages; it can be used when the image contains both random noise and shading. Furthermore, this method takes into account the notion of “hanging togetherness” of image elements; a missing concept in other researches. The next part is a brief explanation of the process for obtaining fuzzy-connected 2D image segmentation.

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