Kansei Image Retrieval Based on ROI Extracted by Color and Entropy
利用颜色和熵提取感兴趣区域的感性图像检索

Kansei image retrieval is a new kind of retrieval technology with high complexity.However,(it's) likely that only some parts of the image would attract people and produce affections.Color imposes a great impact upon the feeling as the basic feature of image,and the difference and comparison of the color would make people produce different kansei.Meanwhile,the entropy of the image also exhibits the information quantity and is a measurement of arousing (people's) kansei.In this paper,we present a method of kansei image retrieval utilizing the color and entropy to extract region of interest(ROI).Back propagation neural network is employed to map the color and entropy of ROI to affective feature space.Finally,we show some experimental results.