A Comparative Evaluation of Retrieval Methods for Duplicate Search in Image Database

Abstract Visual database systems are continuously enriched by original and processed images derived from the original using editing techniques. This last type of image (called duplicate) represents a relevant quote of unnecessary stored images and, moreover a clear case of image similarity. In this paper a comparative evaluation between image retrieval methods in the specific case of duplicate search is proposed. All methods are based on low-level features extraction, such as colors, shape and patterns, and are suitable in automatic systems. The performance comparison is made in terms of effectiveness using a database of 6368 natural pictures and 12 test sets of 18 images each.

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