Human-Inspired Order-based Block Feature in the HSI Color Space for Image Retrieval
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 blocks color features. Thirdly, block features of the same statistical value in the same row are sorted in ascending order to form a rows features. Finally, all row features are concatenated to form an images color feature. The experimental results show that the OBCF method provides high retrieval accuracy compared with color histogram method.
Hong Qin Shoujue Wang Huaxiang Lu Xinliang Chen
Institute of Semiconductors,Chinese Academy of Sciences,Beijing,China
国际会议
2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)
桂林
英文
1978-1982
2009-12-19（万方平台首次上网日期，不代表论文的发表时间）