Segmentation of touching insects based on optical flow and NCuts

Counting the number of rice pests captured via light traps each day is very important for monitoring the population dynamics of rice pests in paddy fields. This paper focuses on developing a segmentation method for separating the touching insects in the rice light-trap insect image from our imaging...

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Published in:	Biosystems engineering Vol. 114; no. 2; pp. 67 - 77
Main Authors:	Yao, Qing, Liu, Qingjie, Dietterich, Thomas G., Todorovic, Sinisa, Lin, Jeffrey, Diao, Guangqiang, Yang, Baojun, Tang, Jian
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01-02-2013 Elsevier
Subjects:	Agricultural machinery and engineering Agronomy. Soil science and plant productions Biological and medical sciences Fundamental and applied biological sciences. Psychology Generalities. Biometrics, experimentation. Remote sensing glass image analysis insects light traps monitoring paddies pests population dynamics rice watersheds Bioengineering Engineering Segmentation Arthropoda Insecta Agriculture Invertebrata
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Abstract	Counting the number of rice pests captured via light traps each day is very important for monitoring the population dynamics of rice pests in paddy fields. This paper focuses on developing a segmentation method for separating the touching insects in the rice light-trap insect image from our imaging system to automatically identify and count rice pests by photographing them on a glass table. When placed on the glass, many specimens may be touching, which interferes with automated identification. To segment touching insects, this paper describes a method in which the glass table is lightly tapped between successive images, which causes the specimens to move slightly. Optical flow is computed between the two images captured before and after insect motion. Normalized cuts (NCuts), with the optical flow angle as the weight function, was applied to separate the touching insects according to the number of insects in each connected region. We compare our method with the k-means and watershed methods. Our method achieves an average rate of good segmentations of 86.9%. In our future work, we will focus on the identification and counting of rice light-trap pests. ► The goal of this work is to segment the touching insects by image processing. ► Insects move slightly by tapping the glass table for successive images. ► Optical flow is used to detect the moving insects by two successive images. ► k-means, watershed and NCuts are used to separate the touching insects. ► NCuts based on optical flow angle achieves better segmentation result.
AbstractList	Counting the number of rice pests captured via light traps each day is very important for monitoring the population dynamics of rice pests in paddy fields. This paper focuses on developing a segmentation method for separating the touching insects in the rice light-trap insect image from our imaging system to automatically identify and count rice pests by photographing them on a glass table. When placed on the glass, many specimens may be touching, which interferes with automated identification. To segment touching insects, this paper describes a method in which the glass table is lightly tapped between successive images, which causes the specimens to move slightly. Optical flow is computed between the two images captured before and after insect motion. Normalized cuts (NCuts), with the optical flow angle as the weight function, was applied to separate the touching insects according to the number of insects in each connected region. We compare our method with the k-means and watershed methods. Our method achieves an average rate of good segmentations of 86.9%. In our future work, we will focus on the identification and counting of rice light-trap pests. Counting the number of rice pests captured via light traps each day is very important for monitoring the population dynamics of rice pests in paddy fields. This paper focuses on developing a segmentation method for separating the touching insects in the rice light-trap insect image from our imaging system to automatically identify and count rice pests by photographing them on a glass table. When placed on the glass, many specimens may be touching, which interferes with automated identification. To segment touching insects, this paper describes a method in which the glass table is lightly tapped between successive images, which causes the specimens to move slightly. Optical flow is computed between the two images captured before and after insect motion. Normalized cuts (NCuts), with the optical flow angle as the weight function, was applied to separate the touching insects according to the number of insects in each connected region. We compare our method with the k-means and watershed methods. Our method achieves an average rate of good segmentations of 86.9%. In our future work, we will focus on the identification and counting of rice light-trap pests. ► The goal of this work is to segment the touching insects by image processing. ► Insects move slightly by tapping the glass table for successive images. ► Optical flow is used to detect the moving insects by two successive images. ► k-means, watershed and NCuts are used to separate the touching insects. ► NCuts based on optical flow angle achieves better segmentation result.
Author	Yao, Qing Lin, Jeffrey Tang, Jian Todorovic, Sinisa Dietterich, Thomas G. Diao, Guangqiang Liu, Qingjie Yang, Baojun
Author_xml	– sequence: 1 givenname: Qing surname: Yao fullname: Yao, Qing email: Qingyaozstu@gmail.com organization: School of Informatics Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, PR China – sequence: 2 givenname: Qingjie surname: Liu fullname: Liu, Qingjie email: liuqingjie2@163.com organization: School of Informatics Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, PR China – sequence: 3 givenname: Thomas G. surname: Dietterich fullname: Dietterich, Thomas G. email: tgd@eecs.oregonstate.edu organization: School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97330, USA – sequence: 4 givenname: Sinisa surname: Todorovic fullname: Todorovic, Sinisa email: sinisa@eecs.oregonstate.edu organization: School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97330, USA – sequence: 5 givenname: Jeffrey surname: Lin fullname: Lin, Jeffrey email: linjy0113@gmail.com organization: School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97330, USA – sequence: 6 givenname: Guangqiang surname: Diao fullname: Diao, Guangqiang email: diaoguangqiang@126.com organization: School of Informatics Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, PR China – sequence: 7 givenname: Baojun surname: Yang fullname: Yang, Baojun email: ybjhz@yahoo.com.cn organization: State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, PR China – sequence: 8 givenname: Jian surname: Tang fullname: Tang, Jian email: tangjian@mail.hz.zj.cn organization: State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, PR China
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Snippet	Counting the number of rice pests captured via light traps each day is very important for monitoring the population dynamics of rice pests in paddy fields....
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SubjectTerms	Agricultural machinery and engineering Agronomy. Soil science and plant productions Biological and medical sciences Fundamental and applied biological sciences. Psychology Generalities. Biometrics, experimentation. Remote sensing glass image analysis insects light traps monitoring paddies pests population dynamics rice watersheds
Title	Segmentation of touching insects based on optical flow and NCuts
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