Friday 24th of November 2017
 

Study of Edge Detection Based On 2D Entropy


Mohamed A. El-Sayed

Edges of an image are considered a type of crucial information that can be extracted by applying detectors with different methodology. It is a main tool in pattern recognition, image segmentation, edge detection and scene analysis. In this paper, we present a new technique of edge detection based on two-dimensional Tsallis entropy. The two-dimensional Tsallis entropy was obtained from the two-dimensional histogram which was determined by using the gray value of the pixels and the local average gray value of the pixels, the work it was applied a generalized entropy formalism that represents a recent development in statistical mechanics. The effectiveness of the proposed method is demonstrated by using examples from the real-world and synthetic images. The performance evaluation of the proposed technique in terms of the quality of the edge images are presented.

Keywords: Tsallis entropy, Edge detection, image segmentation, 2D histogram

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ABOUT THE AUTHOR

Mohamed A. El-Sayed
Math Dept, Faculty of Science, Fayoum University, Fayoum, Egypt, Computer Science Dept, CIT College, Taif Univesity, KSA


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