A Research On Machine Vision System Capability Evaluation Based On Pixels

With the popularization of intelligent large-scale production,and the demand of people for high product quality is growing,the traditional artificial visual detection has been unable to meet the requirements of production with automation and high quality,so,machine vision measuring system is appeared to solve this problem.In order to ensure the reliability of machine vision system to detect products,it is necessary to evaluate the capability of machine vision system.For the effective evaluation of machine vision measurement system,imaged processing technology is used to evaluate the capability of machine vision system(MVS),which is used to take photos of irregular products similar to the rectangular or oval.The original image data are processed by noise reduction,grayness and image segmentation technology to divide image into two parts,target region and background region.The number of pixels and the number of pixels at the boundary of the target region are considered as quality characteristics to determine whether the products are qualified or not,with analysis of the possible factors affecting its quality characteristics,the capability of MVS can be evaluated.The machine vision system for obtaining chip images is analyzed to verify the validity of this method.The chip image data are processed and the number of pixels and the number of pixels at the boundary of the chip region are considered as quality characteristics to determine whether the chip is qualified or not.Then the possible factors such as row,column,angle and the chip itself affecting quality characteristics are analyzed to evaluate the capability of MVS.By compared with evaluation results of the machine vision system in other paper,the reasons for different results are analyzed,and suggestions for improvement are given.