Analysis of Fuzzy Techniques in Edge Detection

Edge detection, which identifies the utmost boundary between two areas with distinct characteristics, is a foundational challenge in computer vision. The ambiguity inherent in this detection–like the blurred transition zone due to image discretization or factors like noise and varying lighting–warrants an approach grounded in fuzzy logic theory. This study offers a comprehensive review of edge detection methods that utilize fuzzy logic, drawing from two academic databases: Scopus and Web Of Science. Out of the systematic literature review, 34 papers were chosen, and their methodologies were outlined in this investigation. The review revealed that in recent times, fuzzy logic has been integrated with other methods to enhance the efficiency of existing techniques or to minimize computational demands. Research using advanced interval fuzzy logic has been adopted for its superior adaptability in addressing the uncertainties inherent in edge detection.