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Edge detection of images is one of the basic and most significant operations in image processing and is used for object background separation, 3-D interpretation of a 2-D image, and pre-processing in image understanding and recognition algorithms. In this paper, the authors investigate cellular automata linear rules for edge detection and based on this investigation they have classified the rules into no edge detection rules, strong edge detection rules and weak edge detection rules. Finally, they show the comparative analysis of the proposed technique with already defined techniques for edge detection and the results show desirable performance.
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