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Proceedings Paper

Application of scan line filling to leaf image segmentation of sugarcane red rot disease
Author(s): Jinhui Zhao; Muhua Liu; Mingyin Yao
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Paper 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%.

Paper Details

Date Published: 10 July 2009
PDF: 5 pages
Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 748913 (10 July 2009); doi: 10.1117/12.836871
Show Author Affiliations
Jinhui Zhao, Jiangxi Agricultural Univ. (China)
Muhua Liu, Jiangxi Agricultural Univ. (China)
Mingyin Yao, Jiangxi Agricultural Univ. (China)

Published in SPIE Proceedings Vol. 7489:
PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering
Honghua Tan; Qi Luo, Editor(s)

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