DESIGN AND ANALYSIS OF FUZZY MORPHOLOGICAL ALGORITHMS FOR IMAGE-PROCESSING

A general paradigm for lifting binary morphological algorithms to fuzz y algorithms is employed to construct fuzzy versions of classical bina ry morphological operations, The lifting procedure is based upon an ep istemological interpretation of both image and filter fuzzification. A lgorithms are designed via the paradigm for various fuzzifications and their performances are analyzed to provide insight into the kind of l iftings that produce suitable results, Algorithms are discussed for th ree image processing tasks: shape detection, edge detection, and clutt er removal, Detailed analyses are given for the effect of noise and it s mitigation owing to fuzzy approaches, It is demonstrated how the fuz zy hit-or-miss transform can be used in conjunction with a decision pr ocedure to achieve word recognition.