Merged-color histogram for color image retrieval

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

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Detail(s)

Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
PagesIII/949-III/952
Volume3
Publication statusPublished - 2002

Publication series

Name
Volume3

Conference

TitleInternational Conference on Image Processing (ICIP'02)
PlaceUnited States
CityRochester, NY
Period22 - 25 September 2002

Abstract

In conventional histogram-based image retrieval algorithms, they usually only find the intersection areas of the color-component distributions of images and thus work well in matching images with exact colors instead of similar colors, especially for computer generated pictures. This could be greatly affected by the overall variation, such as intensity change. In this paper, a novel merged-color histogram (MCH) method for color image retrieval is proposed to facilitate the matching between similar colors by means of color quantization and palette merging. In color quantization, it compacts the color information and matches each color instead of color components, and thus matching of similar colors are accomplished by using palette merging. Experimental results show that the proposed MCH method achieves about 11-32% more precise in the first 20 retrievals for the same image query, and is able to recall 14%-23% more relevant images in the first 100 retrievals, as compared to the conventional RGB-based histogram method.

Citation Format(s)

Merged-color histogram for color image retrieval. / Wong, Ka-Man; Cheung, Chun-Ho; Po, Lai-Man.

IEEE International Conference on Image Processing. Vol. 3 2002. p. III/949-III/952.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review