Interpretation of image segmentation in terms of justifiable granularity

Abstract

The principle of justifiable granularity, as formulated in [1], defines intuitively motivated requirements for an information granule to be meaningful. In the paper, granulation of images obtained by their segmentation is considered. In this context, such concepts as representation of granules and their relations, representation of concepts, consideration of context, detection and treatment of outliers, and recognition method, are of importance. The granular approach is related to intelligent analysis of all kinds of data, not only the computer images.