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| Automated Counting of Rice Planthoppers in Paddy Fields Based on Image Processing |
| YAO Qing, XIAN Ding-xiang, LIU Qing-jie, YANG Bao-jun, DIAO Guang-qiang , TANG Jian |
1、School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, P.R.China
2、State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, P.R.China |
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摘要 A quantitative survey of rice planthoppers in paddy fields is important to assess the population density and make forecasting decisions. Manual rice planthopper survey methods in paddy fields are time-consuming, fatiguing and tedious. This paper describes a handheld device for easily capturing planthopper images on rice stems and an automatic method for counting rice planthoppers based on image processing. The handheld device consists of a digital camera with WiFi, a smartphone and an extrendable pole. The surveyor can use the smartphone to control the camera, which is fixed on the front of the pole by WiFi, and to photograph planthoppers on rice stems. For the counting of planthoppers on rice stems, we adopt three layers of detection that involve the following: (a) the first layer of detection is an AdaBoost classifier based on Haar features; (b) the second layer of detection is a support vector machine (SVM) classifier based on histogram of oriented gradient (HOG) features; (c) the third layer of detection is the threshold judgment of the three features. We use this method to detect and count whiteback planthoppers (Sogatella furcifera) on rice plant images and achieve an 85.2% detection rate and a 9.6% false detection rate. The method is easy, rapid and accurate for the assessment of the population density of rice planthoppers in paddy fields.
Abstract A quantitative survey of rice planthoppers in paddy fields is important to assess the population density and make forecasting decisions. Manual rice planthopper survey methods in paddy fields are time-consuming, fatiguing and tedious. This paper describes a handheld device for easily capturing planthopper images on rice stems and an automatic method for counting rice planthoppers based on image processing. The handheld device consists of a digital camera with WiFi, a smartphone and an extrendable pole. The surveyor can use the smartphone to control the camera, which is fixed on the front of the pole by WiFi, and to photograph planthoppers on rice stems. For the counting of planthoppers on rice stems, we adopt three layers of detection that involve the following: (a) the first layer of detection is an AdaBoost classifier based on Haar features; (b) the second layer of detection is a support vector machine (SVM) classifier based on histogram of oriented gradient (HOG) features; (c) the third layer of detection is the threshold judgment of the three features. We use this method to detect and count whiteback planthoppers (Sogatella furcifera) on rice plant images and achieve an 85.2% detection rate and a 9.6% false detection rate. The method is easy, rapid and accurate for the assessment of the population density of rice planthoppers in paddy fields.
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Received: 26 March 2014
Accepted:
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| Fund: the support of the National Natural Science Foundation of China (31071678), the National High Technology Research and Development Program of China (863 Program, 2013AA102402) and Zhejiang Provincial Natural Science Foundation of China (LY13C140009). |
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Corresponding Authors:
YAO Qing, Tel: +86-571-86843324, E-mail: q-yao@zstu.edu.cn; TANG Jian, Tel: +86-571-63370331, E-mail: tangjian@caas.cn
E-mail: q-yao@zstu.edu.cn; tangjian@caas.cn
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Cite this article:
YAO Qing, XIAN Ding-xiang, LIU Qing-jie, YANG Bao-jun, DIAO Guang-qiang , TANG Jian.
2014.
Automated Counting of Rice Planthoppers in Paddy Fields Based on Image Processing. Journal of Integrative Agriculture, 13(8): 1736-1745.
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