A Study of Low Level Feature Extraction Techniques Used for Content-Based Image Retrieval System
Abstract
Due to the enormous increase in digital image sizes, many Content Based Image Retrieval (CBIR) systems have been developed over the last 10 years in the field of computer vision. Most current issue in CBIR is to extract the set of features that effectively way to represent the image contents. Such afeature extraction requires a detailed evaluation of retrieval performance of image features.The articleis composed of 4 sections: Section 1 gives an introduction into the system of CBIR. Section 2 gives a review of available literature infundamental aspects of content based image retrieval. CBIR method uses various visual features of images such as color, shape, textureetc. Section 3 explainsthe various approachesof similarity measures for the matching of image retrieval. Last section is concluded the possible research directions in CBIR. The problem still remains unsolved, many research attempting to find a suitable method for developingthe system of image retrieval. Since this problem remains unsolved, many research in image retrieval attempt to find the new framework to characterize the image content with higher level semantics, closer to that familiar to the user in mind.
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