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( Hoyoung Lee ),( Chun Chieh Yang ),( Moon S. Kim ),( Jongguk Lim ),( Byoung Kwan Cho ),( Alan Lefcourt ),( Kuanglin Chao ),( Colm D. Everard ) 한국농업기계학회 2014 바이오시스템공학 Vol.39 No.2
Purpose: A multispectral algorithm for detection and differentiation of defective (defects on apple skin) and normal Red Delicious apples was developed from analysis of a series of hyperspectral line-scan images. Methods: A fast line-scan hyperspectral imaging system mounted on a conventional apple sorting machine was used to capture hyperspectral images of apples moving approximately 4 apples per second on a conveyor belt. The detection algorithm included an apple segmentation method and a threshold function, and was developed using three wavebands at 676 nm, 714 nm and 779 nm. The algorithm was executed on line-by-line image analysis, simulating online real-time line-scan imaging inspection during fruit processing. Results: The rapid multispectral algorithm detected over 95% of defective apples and 91% of normal apples investigated. Conclusions: The multispectral defect detection algorithm can potentially be used in commercial apple processing lines.
A Simple Multispectral Imaging Algorithm for Detection of Defects on Red Delicious Apples
Lee, Hoyoung,Yang, Chun-Chieh,Kim, Moon S.,Lim, Jongguk,Cho, Byoung-Kwan,Lefcourt, Alan,Chao, Kuanglin,Everard, Colm D. Korean Society for Agricultural Machinery 2014 바이오시스템공학 Vol.39 No.2
Purpose: A multispectral algorithm for detection and differentiation of defective (defects on apple skin) and normal Red Delicious apples was developed from analysis of a series of hyperspectral line-scan images. Methods: A fast line-scan hyperspectral imaging system mounted on a conventional apple sorting machine was used to capture hyperspectral images of apples moving approximately 4 apples per second on a conveyor belt. The detection algorithm included an apple segmentation method and a threshold function, and was developed using three wavebands at 676 nm, 714 nm and 779 nm. The algorithm was executed on line-by-line image analysis, simulating online real-time line-scan imaging inspection during fruit processing. Results: The rapid multispectral algorithm detected over 95% of defective apples and 91% of normal apples investigated. Conclusions: The multispectral defect detection algorithm can potentially be used in commercial apple processing lines.