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Use of Low Level Features for Content Based Image Retrieval: Survey

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Author Affiliations

  • 1Department of Computer Science, COMSATS Institute of Information Technology, PAKISTAN

Res. J. Recent Sci., Volume 2, Issue (11), Pages 65-75, November,2 (2013)

Abstract

Survey paper reviews the fundamental theories of Content Based Image Retrieval algorithms and development in this field. These algorithms retrieve the digital images from large image database. Image is retrieved from the low level visual content features of query image that is color, texture, shape and spatial location. First we review the visual content description of image and then the fundamental schemes for content based image retrieval are discussed. We also address the comparison of query image and target image of large data base with the indexing scheme to retrieve the image. Relevance feedback in CBIR system is a dominant technique for the retrieval of image which is derived from user’s feedback iteration process. Lastly we discuss the evaluation and semantic gap. In the concluding section we mention our views on role of similarity function with learning and interaction, the problem of evaluation and semantic gap as well as future research directions.

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