In the research of rice appearance quality detection based on visual processing,the segmentation of adhesive rice grains and the recognition and segmentation of chalky rice grains have attracted researchers'attention in recent years.However,there is rare report on how to accurately perform these two different types of segmentation and fuse the results together to provide a complete rice appearance quality detection system yet.Based on this,in this pa-per,a rice appearance quality detection model based on vision fusion was proposed first,it included three modules:rice contour segmentation,rice chalkiness region segmentation and post-processing.Secondly,an automatic detec-tion system based on this model was designed,it could not only calculated chalkiness degree,chalkiness grain rate,broken rice rate,and yellow rice rate directly,but also visualized detection results before and after visual fusion.The experimental results demonstrated that the proposed model could detect the appearance quality of rice completely on the basis of pixel-level segmentation,and the average recognition accuracy for chalkiness degree,chalkiness grain rate,broken rice rate,and yellow rice rate reached 94.5％,96.3％,97.9％and 95.1％,respectively.
NETL
NSTL
万方数据
