Computer Science ›› 2013, Vol. 40 ›› Issue (7): 280-282.

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Grain Classification Based on Edge Feature

LIU Chun-li and ZHANG Gong   

  • Online:2018-11-16 Published:2018-11-16

Abstract: This paper proposed an object detection approach using edge detection.Firstly,it uses dynamic edge detection algorithm to extract the grain edge,secondly,computes the distance between the edge points and the center of gravity,and obtains a vector as the primitive feature which will be processed via amplitude and length normalization and become the feature.The features are used to train the SVM classifier.At last,we conducted simulation experiments using grain image,and the experiment results reveal that the proposed method can efficiently extract the edge feature,and has higherclassification accurate rate.

Key words: Edge detection,Edge representation,Feature extraction,SVM classifier

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