Advanced Content Based Image Retrieval using Gravitational Search Algorithm
Keywords:
semantic gap, content based image retrieval, visual features, gravitational search algorithm (GSA).Abstract
Digital image libraries and other multimedia databases have been dramatically expanded in recent years. Semantic gap that between the visual features and human semantics has become very important area of research known as content based image retrieval (CBIR). In order to effectively and precisely retrieve the desired images from a large image database, the development of a content-based image retrieval (CBIR) system has become an important research issue. The need for improving the retrieval accuracy of image retrieval systems and narrowing down the semantic gap is high in view of the fast growing need of image retrieval. In this paper we review, a user-oriented technique for CBIR method based on low level visual features and gravitational search algorithm (GSA). Before applying the visuality features we have divided the images into kxk blocks and a block wise comparison has been done. Color attributes like the mean value, the standard deviation, and the image bitmap of a color image are used as the features for retrieval. In addition, the entropy based on the gray level co-occurrence matrix considered as the texture features and the Canny edge detection technique for image can be considered as edge features. Finally, some future research directions and problems of image retrieval are presented.
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