Area morphological segmentation for content based retrieval
Content based retrieval (CBR) has emerged as a useful tool for management of digital image libraries. Traditional approaches based on metadata and global features are limited in effectiveness and suffer from various drawbacks involving the use of heuristics and postprocessing techniques. The automated segmentation technique presented is based on fuzzy clustering in a scaled texture space, which is generated via a bank of Gabor filters. Within the texture space, we scale the responses using the novel tool of area morphology. The segmentation algorithm provides segments satisfying a minimum scale requirement for use in CBR. The experiments indicate that our segmentation mechanism increases feature relevancy and reduces the computational costs of segment based matching.