Identification of Multiobjective Rice Lighttrap Pests Based on Template Matching

LV  Jun1 , YAO  Qing1, LIU  Qingjie1, XUE  Jie1, CHEN  Hongming3, YANG  Baojun2, TANG Jian2,*

doi:10.3969/j.issn.10017216.2012.05.016

Chinese Journal OF Rice Science >

2012 , Vol. 26 >Issue 5: 619 - 623

DOI: https://doi.org/10.3969/j.issn.10017216.2012.05.016

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Identification of Multiobjective Rice Lighttrap Pests Based on Template Matching

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¹ College of Informatics and Electronics, Zhejiang SciTech University, Hangzhou 310018, China; ² China National Rice Research Institute, Hangzhou 310006, China; ³ Xiangshan County Plant Protection and Quarantine Station, Xiangshan 315700, China;

Received date: 2011-11-16

Revised date: 2012-05-16

Online published: 2012-09-10

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Abstract

Identification and count of rice lighttrap pests are very important in monitoring rice pests. The pests trapped by black light lamps show different postures and incomplete bodies, which increase the difficulty of image automatic identification. Template matching and Kfold cross validation methods were used to identify multiobjective rice lighttrap pests based on nontouching pest images. Firstly, one hundred and fiftysix features including color, shape and texture features were extracted from each pest image. Secondly, the principal component analysis was employed for reducing data dimensionality, and first six principal components were selected as pests’ features. Then, the template number was determined according to the gesture of each pest species and the template parameters were obtained from the cluster centers by fuzzy Cmean clustering method. Finally, single and multitemplate matching methods were used to identify rice pests. The results showed that the accurate rate of multitemplate matching and single template matching were 83.1% and 59.9%, respectively for rice lighttrap pests with multiple postures and some incomplete bodies.

Key words： rice lighttrap pest; pest identification; image processing; feature extraction; template matching

Cite this article

LV Jun1 , YAO Qing1, LIU Qingjie1, XUE Jie1, CHEN Hongming3, YANG Baojun2, TANG Jian2,* . Identification of Multiobjective Rice Lighttrap Pests Based on Template Matching[J]. Chinese Journal OF Rice Science, 2012 , 26(5) : 619 -623 . DOI: 10.3969/j.issn.10017216.2012.05.016

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