Visual Texture Classification Using Fuzzy Inference

A fuzzy rule-based system for visual texture classification is presented. Fuzzy rule-based classifiers can be conveniently high interpretable for the end user. The proposed classification system is built in two phases: learning and recognition. In the learning phase, each texture class is modeled by a particular rule that includes linguistic terms obtained through a fuzzification of some visual features. For recognition purposes, an unknown texture image is subject to an inference process, and it is labeled as the class whose rule score is the highest. Experiments using a set of reference textures result on good classification rates. Visual Texture, Fuzzy inference, Rule-based classification.