80%。An online classification system was developed based on automated visual inspection (AVI) technology to classify the foreign fibers detected in cotton. The proposed system uses a lint layer generator to bring the foreign fibers buried inside the lint to the surface, to make them easy to be “seen”. A Piranha color camera with a tri-linear CCD sensor was used to detect color foreign fibers, and a Piranha2 line scan CCD camera was employed to detect the white foreign fibers which can emit fluorescence under the ultraviolet excitation. Then a fuzzy classifier integrating multiple classifiers was designed for the classification of the detected foreign fibers. The results indicate that the mean veracity of classification of foreign fibers reaches 80%.
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杨文柱,李道亮,魏新华,康玉国,李付堂.基于自动视觉检测的棉花异性纤维分类系统[J].农业机械学报,2009,40(12):177-181. for Classification of Foreign Fibers in Cotton[J]. Transactions of the Chinese Society for Agricultural Machinery,2009,40(12):177-181.