基于图像清晰度评价的磨削表面粗糙度检测方法

针对当前机器视觉检测粗糙度主要采用图像灰度值信息进行统计分析,没有充分利用色彩信息且忽略了人眼视觉系统主观评判的问题,提出一种基于图像清晰度评价的磨削表面粗糙度检测方法。根据色块在不同等级粗糙度表面上形成的图像清晰度不一样,采用熵函数评价算法和基于色彩相关性的彩色图像清晰度评价算法分别构建清晰度与粗糙度之间的关系模型,论证了基于图像清晰度检测磨削表面粗糙度方法的可行性。试验结果表明,基于图像清晰度检测磨削表面粗糙度是一种可行的粗糙度检测方法,清晰度与粗糙度相关性强,清晰度有随着粗糙度的增大而减小的趋势,且利用色彩相关性的彩色图像清晰度评价算法对磨削表面粗糙度检测具有较好的灵敏性,并且该方法符合人眼视觉系统的主观评价;清晰度算法和主观评价二者结合可快速简易地在线检测工件的整体表面轮廓粗糙度。

Detection Method of Grinding Surface Roughness Based on Image Definition Evaluation

A novel method to detect the grinding surface roughness based on image definition was proposed to solve the problem that the current machine vision detected roughness mainly by adopting image grey value information for statistical analysis, not making full use of color information, and also ignoring the problem of the subjective evaluation of human visual system. According to the phenomenon that the image definition formed on the different grade roughness surface of different color pieces is different, the article built a relational model between resolution and roughness by using two resolution evaluation algorithms, which including the entropy function evaluation algorithm and the color image evaluation algorithm based on color correlation, respectively, to demonstrate the feasibility of the detection method proposed. The experimental results show that the detection method is feasible, the relevance between resolution and roughness is strong, the resolution is decreased while the roughness is increased, and the color image evaluation algorithm based on color correlation is better sensitive. Meanwhile, the idea of the proposed method conforms to the subjective evaluation of human eye vision system, the method combined resolution algorithm with subjective evaluation can detect the whole surface profile roughness of workpiece on-line quickly.