Histogram Matching Algorithm for Content-Based Image Retrieval 


Vol. 33,  No. 1, pp. 45-52, Jan.  2008


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  Abstract

In this paper, we describe the Perceptually Weighted Histogram (PWH) and the Gaussian Weighted Histogram Intersection (GWHI) algorithms. These algorithms are able to provide positive results in image retrieval. But these histogram methods alter the histogram of an image by using particular lighting conditions. Even two pictures with little differences in lighting are not easily matched. Therefore, we propose that the Histogram Matching Algorithm (HMA) is able to overcome the problem of an image being changed by the intensity or color in the image retrieval. The proposed algorithm is insensitive to changes in the lighting. From the experiment results, the proposed algorithm can achieve up to 32% and up to 30% more recall than the PWH and GWHI algorithms, respectively. Also, it can achieve up to 38% and up to 34% more precision than PWH and GWHI, respectively. Therefore, with our experiments, we are able to show that the proposed algorithm shows limited variation to changes in lighting.

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  Cite this article

[IEEE Style]

K. S. You, G. Yoo, H. S. Kwak, "Histogram Matching Algorithm for Content-Based Image Retrieval," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 1, pp. 45-52, 2008. DOI: .

[ACM Style]

Kang Soo You, Gi-Hyoung Yoo, and Hoon Sung Kwak. 2008. Histogram Matching Algorithm for Content-Based Image Retrieval. The Journal of Korean Institute of Communications and Information Sciences, 33, 1, (2008), 45-52. DOI: .

[KICS Style]

Kang Soo You, Gi-Hyoung Yoo, Hoon Sung Kwak, "Histogram Matching Algorithm for Content-Based Image Retrieval," The Journal of Korean Institute of Communications and Information Sciences, vol. 33, no. 1, pp. 45-52, 1. 2008.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880