Research of Image Retrieval Based on Feedback Mechanism

We first research the low-layer physical feature of image, retrieval the image by color features, and import the technique of relevance feedback. By cooperation between human and computer, Making up the computer's limited ability of understanding and enhancing the effect of retrieval. The key techniques of relevance feedback and semantic query are the important mark that the technique of CBIR develops from low-grade to high-grade. So the research of this paper has important meaning in learning value and practice application. When extracting the low-layer physical feature of image, along with the analysis of HSV color space, we propose a new 20 color none uniform quantization method based on HSV space, which is more reasonable to human's vision model. Comparing with The traditional color quantization methods, the storage space and calculation decrease and not sensitive to light. Its query performance is better than traditional color quantization methods.