关键词: 表面粗糙度, 机器视觉测量, 四元数, 奇异值熵, 颜色信息

Abstract: Most of the evaluation indices used in measuring surface roughness by machine vision were statistical analyzed based on gray scale image information， while some evaluation indices based on color information did not provide reasonable mathematical structure expression in current studies.Aiming at these problems， a detection method was proposed based on singular value entropy of color images to evaluate the roughness of ground surfaces.According to the differences of the energy distribution of the virtual image formed by the color-block on the surfaces with different levels of roughness， a pure quaternion data structure was used to characterize a color image and the data was analyzed. The singular value entropy was extracted as the evaluation index， and the feasibility of evaluating ground surface roughness was demonstrated based on singular value entropy index.The experimental results show that the singular value entropy of color images is a reasonable and feasible surface roughness evaluation index， and has a reasonable data structure expression in a mathematical sense. The comparative analysis of relevant index proves that the correlation and applicability of the index with surface roughness are stronger than that of the color difference index， and the regression prediction results are relatively accurate and have the potential to be extended to the field of engineering applications.

Key words: surface roughness, machine vision measurement, quaternion, singular value entropy, color information