A pigment separation method of centralized image channel difference based on optical density space

Abstract

The invention discloses a pigment separation method of centralized image channel difference based on optical density space, which comprises the following steps of acquiring an RGB color skin image under polarized light and extracting skin color; dividing the image into a plurality of sub-image blocks and discarding the sub-image blocks containing non-skin pixels; obtaining the pure color density of each sub-image block; obtaining a matrix optimum solid color concentration matrix; calculating the concentrations of melanin and hemoglobin in the image, and introducing the gray distribution and color distribution of the pigment concentration. According to the present invention, a light source interference term in a conventional pigment separation model is eliminated without principal componentanalysis, and a simple and efficient constraint condition for judging the rationality of the pure color concentration matrix is designed, thereby avoiding, in the existing pigment separation algorithm, the inaccuracy and robustness of the pigment concentration extraction result due to the interference of light source intensity and the data loss in the principal component analysis process, as wellas the low efficiency of the algorithm due to the complexity of the determination process of the pure color concentration matrix.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and more specifically relates to a pigment separation method based on a centralized image channel difference in optical density space, which is used for extracting the concentrations of melanin and hemoglobin from RGB color skin images. Background technique [0002] Melanin (Melanin) and hemoglobin (Hemoglobin), as the two most abundant and most important pigments in human skin, their concentration directly affects the health of the skin. The disturbance of the concentration of these two pigments may lead to various pigment diseases (such as freckles, chloasma, etc.), skin inflammation, and even skin cancer. Therefore, monitoring the concentration changes of hemoglobin and melanin is of great significance to the diagnosis and treatment of skin diseases and the efficacy test of cosmetics. [0003] Judging from the relevant literature, pigment separation research related to the ca...

AI Technical Summary

Problems solved by technology

The second type combines the tissue structure and optical properties of the skin, simulates and synthesizes different skin colors by changing the pigment concentration, and generates a skin color table, so that the concentration of melanin and hemoglobin can be reversely estimated based on the color of the skin image. The precision of this kind of method to obtain the concentration of pigment is not high

However, the existing pigment separation method fails to eliminate the interference caused by the intensity of the light source in the model and solve the data loss problem caused by the principal component analysis process, which makes the light source robustness of the method poor, and the pigment separation results are not accurate enough. At the same time, the method The execution efficiency is not high

Therefore, the existing pigment separation method is difficult to be practical, and there is a large room for improvement

Images