Primary-view perception on a gray image: region segmentation and association

摘要

The segmentation of scenes into perceptually meaningful partitions possessing a useful relationship among them is of great importance in image understanding. In this paper, an effective approach performing image segmentation and association among the segmented regions for a gray image is presented. An unsupervised segmentation process using a self-organization map (SOM) and spatial-distance computation is presented for the segmentation of clusters in our understanding system. An association process is developed for the construction of spatial relationships among the attended regions, which are obtained from the segmented clusters using fuzzy relations. The algorithms for each process are presented and exemplified with a series of illustrations. This approach is applied to simulating the primary-view perception on a natural gray image. Experiments show that the proposed approach is feasible. A possible linguistic presentation, based on the attended regions and their relationships, is given for every test image.