Application of scan line filling to leaf image segmentation of sugarcane red rot disease

Jinhui Zhao; Muhua Liu; Mingyin Yao

doi:10.1117/12.836871

10 July 2009 Application of scan line filling to leaf image segmentation of sugarcane red rot disease

Jinhui Zhao, Muhua Liu, Mingyin Yao

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%.

Citation Download Citation

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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KEYWORDS

Image segmentation

Feature extraction

Image processing

Image processing algorithms and systems

Detection and tracking algorithms

Agriculture

Machine vision

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