Optimal matching of images using combined color feature and spatial feature

Authors:
Xin Huang;Shijia Zhang;Guoping Wang;Heng Wang
Affiliations:
Human-Computer Interaction & Multimedia Lab, Department of Computer Science and Technology, Peking University, Beijing, P.R. China;Human-Computer Interaction & Multimedia Lab, Department of Computer Science and Technology, Peking University, Beijing, P.R. China;Human-Computer Interaction & Multimedia Lab, Department of Computer Science and Technology, Peking University, Beijing, P.R. China;Human-Computer Interaction & Multimedia Lab, Department of Computer Science and Technology, Peking University, Beijing, P.R. China
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part I
Year:
2006

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Abstract

In this paper we develop a new image retrieval method based on combined color feature and spatial feature. We introduce an ant colony clustering algorithm, which helps us develop a perceptually dominant color descriptor. The similarity between any two images is measured by combining the dominant color feature with its spatial feature. The optimal matching theory is employed to search the optimal matching pair of dominant color sets of any two images, and the similarity between the query image and the target image is computed by summing up all the distances of every matched pair of dominant colors. The algorithm introduced in this paper is well suited for creating small spatial color descriptors and is efficient. It is also suitable for image representation, matching and retrieval.