Emergence Phenomenon Could Be Applied in Meaningful Image Segmentation

Content-based image retrieval is a difficult area of research in multimedia systems. The research has proved extremely difficult because of the inherent problems in proper automated analysis and feature extraction of the image to facilitate proper classification of various objects. An image may contain more than one objects and to segment the image in line with object features to extract meaningful objects and then classify it in high-level like table, chair, car and so on has become a challenge to the researchers in the field. The latter part of the problem, the gap between low-level features like color, shape, texture, spatial relationships and high-level definitions of the images is called the semantic gap. Until we solve these problems in an effective way, the efficient processing and retrieval of information from images will be difficult to achieve. In this paper we explore the possibilities of how emergence phenomena can help us solve these problems of image segmentation and semantic gap.