ITERATIVE FUZZY IMAGE SEGMENTATION

The multispectral signature of features has been used for identification of objects in remotely sensed scenes for a number of years. Recently these techniques have been applied to feature selection in natural scenes. Due to the inherent noise and degradation of the input cues to the algorithms, meaningful image segmentation is a difficult process. In an effort to reduce the sensitivity of a system to these problems, we have been led to the development of a iterative fuzzy clustering technigue for image segmentation. It is believed that this method represents an image segmentation scheme which can be used as a preprocessor for a multivalued logic based computer vision system. This paper presents an iterative algorithm for image segmentation, based on clustering in an image feature space.