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IJSTR >> Volume 1 - Issue 8, September 2012 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Image Segmentation Based On FUZZY GLSC Histogram With Dynamic Similarity Discrimination Factor

[Full Text]

 

AUTHOR(S)

N. Swathi, K. Ravi Kumar

 

KEYWORDS

Keywords :- Entropy, Fuzzyfication, Fuzzyfied image, GLSC histogram, threshold.

 

ABSTRACT

Abstract:- Image pressing applications performes image segmentation as pre-processing technique to extract the features for next stage. The application performance depends on image segmentation, to process the foreground or background objects. The image segmentation plays a vital role in computer vision and image processing applications. Inspite of having many thresholding techniques in literature they have their own limitations. This paper proposes a new method of thresholding using Gray Level Spatial Correlation (GLSC) histogram with a dynamic similarity discrimination factor( ) and Fuzzy logic in deciding the threshold using Shannon\'s entropy. The similarity discrimination factor( ) is made dynamic by considering the absolute difference between the global and local mean of the image. Calculating the threshold in the fuzzyfied region makes the segmentation process the most time efficient than the existing methods. Experimental results proove better efficiency than the existing methods. The technique out performs in case of low contrast images.

 

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