Abstract: Taking peanut kernels as the research object, this study explores visual hardware acquisition devices through experimental research, and ultimately proposes a method for identifying moldy peanut kernels based on binocular vision and the R component of color as the characteristic value. After the target image is captured by a binocular camera and input into the LabVIEW software processing system, the image undergoes preprocessing, grayscale histogram analysis, extraction and analysis of color characteristic values, classifier construction, and matching the extracted color characteristic values of the peanut kernel image with the classifier to complete the identification task. Finally, a moldy peanut kernel identification system is designed. Test results show that the accuracy rate of this method for identifying moldy peanut kernels reaches 95%, basically meeting the standard for moldy peanut kernel detection.
金庆睿, 刘文超, 麻荣欣, 王雪晴. 基于双目视觉的霉变花生粒粒识别研究[J]. 吉林化工学院学报, 2025, 42(7): 89-94.
JIN Qingrui, LIU Wenchao, MA Rongxin, WANG Xueqing. Research on Recognition of Mouldy Peanut based on Binocular Vision. Journal of Jilin Institute of Chemical Technology, 2025, 42(7): 89-94.
