Feature space optimization prior to fuzzy image classification

This paper presents a method for features space optimization in a context of fuzzy image classification. Based on membership functions intersections, the method allows to select the most appropriate features for objects discrimination. Comparison of the eCognition nearest neighbor algorithms and fuzzy classification is provided with the use of un-optimized and optimized features sets.