Volume 8 Number 7 (Jul. 2013)
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JSW 2013 Vol.8(7): 1736-1742 ISSN: 1796-217X
doi: 10.4304/jsw.8.7.1736-1742

Research of Weeds Classification System Based on Shape Feature

Liang Gao1, Dongming Li2, Yihua Zhang3
1Office of Scientific and Technological Management, Agricultural University of Hebei, Baoding 071001, P.R.China
2College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, P.R.China
3Jibei Baoding Electric Power VOC. & TECH. College, Baoding, 071051, P.R.China

Abstract—The paper studied weeds classification system using BP neural network and 6 shape parameters (the ratio of the width and the length, complete degrees, the roundness, the rectangle, ratio of the framework proportion and frame perimeter) based on such characteristic parameters as weed leaf area, perimeter, minimum bounding rectangle, circumcircle, equivalent oval as input feature vectors; and meanwhile trained and improved the system. The experiment results showed when the plant coverage was low, the classification system could identify different weeds better; otherwise, the correct recognition rate was lower.

Index Terms—Weeds classification, leaf, shape parameters, neural network, coverage


Cite: Liang Gao, Dongming Li, Yihua Zhang, "Research of Weeds Classification System Based on Shape Feature," Journal of Software vol. 8, no. 7, pp. 1736-1742, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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