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10 July 2009 Application of scan line filling to leaf image segmentation of sugarcane red rot disease
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Proceedings Volume 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering; 748913 (2009) https://doi.org/10.1117/12.836871
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China
Abstract
Red rot disease is a common disease at the seedling stage of sugarcane. In order to identify red rot disease effectively, a segmentation algorithm for leaf images of sugarcane red rot disease using scan line filling is proposed. The proposed algorithm has six stages. During the first stage, the class of green plants is separated from the class of non-green plants using the color feature of 2G-R-B. At the second stage, connected regions of the class of green plants are labeled. At the third stage, outer contours are extracted. At the fourth stage, the regions surrounded by outer contours are filled using scan line filling. At the fifth stage, the images are colorized. At the sixth stage, red rot diseased spots are extracted using the color feature. The experimental results show that this algorithm can extract red rot diseased spots effectively, and the accurate rate of image segmentation for red rot diseases is 96%.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jinhui Zhao, Muhua Liu, and Mingyin Yao "Application of scan line filling to leaf image segmentation of sugarcane red rot disease", Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 748913 (10 July 2009); https://doi.org/10.1117/12.836871
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