Computerized feature quantification of sublingual veins from color sublingual images.

Characteristics of tongue pose the most important information for Traditional Chinese Medicine diagnosis. So far, extensive studies have been made on extracting tongue surface features, but rarely refer to sublingual vein that is also diagnostically important. This paper focuses on establishing a feature quantification framework for the inspection of sublingual veins, composed of two parts: the segmentation of sublingual veins and the feature quantification of them. Pixel-based sublingual vein segmentation algorithm and adaptive sublingual vein segmentation algorithm for color sublingual images with visible contrast and low contrast are proposed respectively. The experiments prove that the proposed algorithms perform well on the segmentation of sublingual veins from color sublingual images with both visible contrast and low contrast. A chromatic system in conformity with diagnostic standard of tongue diagnosis is established to characterize the chromatic feature of sublingual veins. Experimental results reveal that the breadth and chromatic features quantified by the proposed framework are properly consistent with the diagnostic standard summarized by tongue diagnosis.