Fuzzy sets in image processing and recognition

Abstract

The various aspects of image processing and analysis problems where the theory of fuzzy set has so far been applied are addressed along with their relevance and applications. The possibility of combining fuzzy set theory, neural network theory and genetic algorithms for improved performance is discussed. The applications include enhancement, edge detection, thinning, segmentation, object extraction, skeleton extraction, primitive extraction, information and ambiguity measures, curve fitting, and the use of neural learning. Some future research directions are outlined. A list of representative references is also provided.<>