Color histogram is an important technique for color database retrieving, but it often ignores color’s spatial distribution information. This paper proposes an improved color histogram algorithm based on the HSV space, whose subspaces are non-equally quantized. The algorithm first proceeds annular partition on the original image, and then uses the method presented by Aibing Rao etc. [1] to count each partition. At last, it calculates the weighted sums for the distances between distinct color histograms. Experimental results demonstrate that the algorithm reduces the feature dimensions and keeps a good accuracy as well as the spatial distribution information. Thus, a better retrieval result is obtained.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.