An efficient technique for retrieval of color images in large databases. (August 2015)

• Record Type: Journal Article
• Authors: Shrivastava, Nishant; Tyagi, Vipin
• Is Part Of: Computers & electrical engineering. Volume 46(2015)
• Page Start: 314
• Page End: 327
• Publication Date: 2015-08
• Subjects: Image retrieval -- Feature vector -- Histogram -- Gabor filter -- CBIR; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2014.11.009
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Traditional image retrieval systems match the input image by searching the whole database repeatedly for various image features. Intermediate results produced for these features are merged using data fusion techniques to produce one common output. In this paper, a new image retrieval technique is presented, which retrieves similar images in three stages. A fixed number of images is first retrieved based on their color feature similarity. The relevance of the retrieved images is further improved by matching their texture and shape features respectively. This eliminates the need of fusion and normalization techniques, which are commonly used to calculate final similarity scores. This reduces the computation time and increases the overall accuracy of the system. Moreover, in this technique, global and region features are combined to obtain better retrieval accuracy. Experimental results on two databases (COREL and CIFAR) have shown that the proposed technique produces better results while consuming less computation time for large image databases.