Tongue Colorchecker for Precise Correction

In order to improve the correction accuracy of tongue colors by use of the Munsell colorchecker, this research aims to design a new colorchecker by aid of the tongue color space. Three essential issues leading to the development of this space-based colorchecker are investigated in this chapter. First, based on a large and comprehensive tongue database, the tongue color space is established by which all visible colors can be classified as tongue or non-tongue colors. Hence, colors of the designed tongue colorchecker are selected from tongue colors to achieve high correction performance. Second, the minimum sufficient number of colors involved in the colorchecker is attained by comparing the correction accuracy when a different number (range from 10 to 200) of colors are contained. Thereby, 24 colors are included because the obtained minimum number of colors is 20. Lastly, criteria for optimal color selection and their corresponding objective function are presented. Two color selection methods, i.e., greedy and clustering-based selection methods, are proposed to solve the objective function. Experimental results show that the clustering-based method outperforms its counterpart to generate the new tongue colorchecker. Compared to the Munsell colorchecker, this proposed space-based colorchecker can improve the correction accuracy by 48%. Further experimental results on more correction tasks also validate its effectiveness and superiority.