Segmentation of touching insects based on optical flow and NCuts

• 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
• ISSN: 1537-5110; 1537-5129
• DOI: 10.1016/j.biosystemseng.2012.11.008

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.