Tongue coating image retrieval

Along with the rapid growth of medical data, image retrieval, a kind of technology for browsing, searching and retrieving similar images of the given image, has become increasingly important from a large database of digital images. Tongue coating is the most important characteristic to reveal the pathological changes of the tongues for identifying diseases. In this paper, an efficient and effective technique is proposed to retrieve coating images. We obtain the pixel template value of pixels by applying thresholding segmentation based relative entropy. Then we use a Reduced K Nearest Neighbor algorithm to extract 20-dimension feature vector based on a prior layout distribution. Finally, a distance based the cumulative ratio is proposed for tongue coating image matching. The experimental results indicate that the proposed scheme eliminates the imprecision and uncertainty associated with medical tongue coating analysis.