Comparative Analysis of EDGE detection using Fuzzy set theory and Automata Theory with existing edge detection methods with CLA
نویسنده
چکیده
In this paper, traditional methods of edge detection and their problems are discussed. After that high performance method for edge detection that is fuzzy logic based image processing is used for accurate and noise free edge detection and Cellular Learning Automata (CLA) is used for enhance the previously-detected edges with the help of the repeatable and neighborhood-considering nature of CLA. In the end, we compare it with popular methods such as Sobel, Canny and Prewitts with enhanced by CLA. Edge is most important visual parameter so if the edges in an image can be identified accurately, all of the objects can be located and basic properties such as area, perimeter, and shape can be measured. In this paper, all the algorithms and result are prepared in MATLAB.
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