Edge detection technique by fuzzy logic and Cellular Learning Automata using fuzzy image processing

Edge is the boundary between an object and the background, and identifies the boundary between overlapping and non-over lapping objects. This means that 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. Here 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. The different result of edge detection technique is compared with fuzzy edge detected and resulting edge is enhanced using CLA. In this paper, all the algorithms and result are prepared in MATLAB.