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標題: Detection and classification of areca nuts with machine vision
作者: Huang, Kuo-Yi
Contributors: Wei Chun Wang
關鍵字: Areca nut;Neural network;Machine vision
日期: 2012-09
Issue Date: 2013-07-02 10:22:08 (UTC+8)
摘要: In this study, we present an application of neural networks and image processing
techniques for detecting and classifying the quality of areca nuts. Defects with diseases
or insects of areca nuts were segmented by a detection line (DL) method. Six geometric
features (i.e., the principle axis length, the secondary axis length, axis number, area,
perimeter and compactness of the areca nut image), 3 color features (i.e., the mean gray
level of an areca nut image on the R, G, and B bands), and defects area were used in the
classification procedure. A back-propagation neural network classifier was employed to
sort the quality of areca nuts. The methodology presented herein effectively works for
classifying areca nuts to an accuracy of 90.9%.
Relation: Computers and Mathematics with Applications, Volume 64, Volume 739–746
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