ISSN : 1796-2048
Volume : 3    Issue : 1    Date : May 2008

Texture Segmentation Methods Based on Combinatorial of Morphological and Statistical Operations
Vakulabharanam Vijaya Kumar, B.Eswara Reddy, A.Nagaraja Rao, and U.S.N.Raju
Page(s): 36-40
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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.

Index Terms
Geometrical features, Dilation, Erosion, Mean, Median, Dynamic, Number of operations and Type of