Extraction of Tongue Crack Based on Gray Level and Texture

Abstract

Tongue diagnosis is one of the most important content of Traditional Chinese Medicine (TCM). While the tongue crack is an important index of tongue diagnosis, there are just a few existing researches of tongue crack extraction and the results of them are unsatisfactory. This paper proposes a new algorithm for tongue crack extraction based on crack’s grayscale and texture in the tongue image. The method analyses and handles the tongue image’s luminance component in HSV color space. Firstly, we use the morphological opening closing reconstruction to eliminate small texture and noise of tongue images. Then we use Bot-hat transform and Otsu adaptive threshold segmentation to extract tongue cracks. Finally, we use correlation and entropy of grayscale symbiotic matrix to screen extracted tongue cracks and realize automatic extraction of tongue cracks. The result has shown that the method can extract tongue cracks with high accuracy and lay a good foundation for subsequent analysis of the crack.