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The Advances of Mathematical Morphology in Image Processing
数学形态学在图象处理中的应用进展

Keywords: dilation,erosion,binary morphology,gray,scale morphology,fuzzy mathematical morphology,soft mathematical morphology,fuzzy soft mathematical morphology
图象处理
,模式识别,计算机,数学形态学

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Abstract:

Mathematical morphology is a methodology of nonlinear filters. The basic morphological operations which stem from Minkowski set operations are dilation and erosion. Mathematical morphology firstly handled binary images as sets and probed them with a structuring element which formed binary morphology, and then gradually formed gray scale morphology, soft mathematical morphology, fuzzy mathematical morphology, and fuzzy soft mathematical morphology. It has been widely used in the area of image processing such as noise suppression, edge detection, image segmentation, feature extraction, nonlinear image filtering and so on. We briefly review some recent advances both in the theory and applications of morphological image analysis.

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