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Texture Segmentation Methods Based on Combinatorial of Morphological and Statistical Operations

Publication Date
  • Geometrical Features
  • Dilation
  • Erosion
  • Mean
  • Median
  • Dynamic
  • Number Of Operations And Type Of Operations
  • Computer Science
  • Mathematics


In this paper we introduce a novel and simple image segmentation schemes that are based on combinations of morphological and statistical operations. Mathematical morphology is very attractive for this purpose because it efficiently deals with geometrical features like as size, shape, contrast or connectivity that can be considered as segmentation oriented features. The present paper derives equations on the basis of dilation, erosion and median or mean which finally results segmentation. The segmentation algorithms are divided into three groups based on number of operations and type of operations, used. Some of the proposed methods of segmentation are useful for edge based segmentation while the other is useful for region based segmentation. The segmentation quality is improved, by dynamically changing the combinatorial coefficients that are used in equations. The present combinatorial method is applied on Brodatz textures and a good segmentation is resulted.

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