International Journal of Computer Vision
Digital Image Processing
An Overview of Content-based Image Retrieval Techniques
AINA '04 Proceedings of the 18th International Conference on Advanced Information Networking and Applications - Volume 2
Diversity in multimedia information retrieval research
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Sum of Values of Local Histograms for Image Retrieval
NCM '08 Proceedings of the 2008 Fourth International Conference on Networked Computing and Advanced Information Management - Volume 02
The Content-Based Image Retrieval Method Using Multiple Features
NCM '08 Proceedings of the 2008 Fourth International Conference on Networked Computing and Advanced Information Management - Volume 01
The PicToSeek WWW Image Search System
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
FSKD '09 Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
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Color is one of the most important descriptor in image processing. Color histogram is the most commonly used color feature and has proved to be stable representation of an image, but it might be similar in different kinds of images because it describe the global intensity distribution of images. Inspired by human image classification behavior, in this paper, a new color feature representation method called Order-based Block Color Feature (OBCF) and its application in image retrieval is proposed. Firstly, RGB values of an image were transferred to HSI values. Secondly, each color channel (H, S and I) of an image is divided into M X N blocks and then statistical values are computed to characterize the block's color features. Thirdly, block features of the same statistical value in the same row are sorted in ascending order to form a row's features. Finally, all row features are concatenated to form an image's color feature. The experimental results show that the OBCF method provides high retrieval accuracy compared with color histogram method.