Content-Based Image Retrieval Benchmarking: Utilizing color categories and color distributions


Broek, Egon L. van den and Kisters, Peter M.F. and Vuurpijl, Louis G. (2005) Content-Based Image Retrieval Benchmarking: Utilizing color categories and color distributions. Journal of Imaging Science and Technology, 49 (3). pp. 293-301. ISSN 1062-3701

open access
Abstract:From a human centered perspective three ingredients for Content-Based Image Retrieval (CBIR) were developed. First, with their existence confirmed by experimental data, 11 color categories were utilized for CBIR and used as input for a new color space segmentation technique. The complete HSI color space was divided into 11 segments (or bins), resulting in a unique CBIR 11 color quantization scheme. Second, a new weighted similarity function was introduced. It exploits within bin statistics, describing the distribution of color within a bin. Third, a new CBIR benchmark was successfully used to evaluate both new techniques. Based on the 4050 queries judged by the users, the 11 bin color quantization proved to be useful for CBIR purposes. Moreover, the new weighted similarity function significantly improved retrieval performance, according to the users.
Item Type:Article
Copyright:© 2011 Society for Imaging Sciences and Technology
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:
Official URL:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page