Most of the research advancements are motivated by market forces or changing customer demands. The demand for effective image retrieval system has been increasing due to massive expansion in volume of digital images on World Wide Web. The necessity to explore huge amount of online multimedia has become a prime reason for boosting development of efficient content based image retrieval algorithms. This paper mainly concentrates on low-level visual features of digital images especially shape features which have been able to reduce the semantic gap between human visual perception and retrieval system`s ability to extract distinct features from image for effective similarity matching. A comprehensive review of recent advancements in shape based image retrieval is presented here, considering different shape features employed by different content based image retrieval systems as focus of study. An outcome of this study is leveraged as a comparative analysis based various computational parameters. This can pose challenges for the researchers and gives directions for future enhancements.

Content-based image retrieval, Review, Semantic gap, Shape features, Shape matching, Shape representation

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