Segmentation method for crop disease leaf images with complex background

Yuan Yuan; Li Miao; Liang Qing; Hu Xiuzhen; Zhang Wei

Volume 27 Issue 2

Feb. 2011

Turn off MathJax

Article Contents

Abstract

Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE) > 2011 > 27(2): 208-212.

Yuan Yuan, Li Miao, Liang Qing, Hu Xiuzhen, Zhang Wei. Segmentation method for crop disease leaf images with complex background[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(2): 208-212.

Citation:

PDF (510 KB)

Segmentation method for crop disease leaf images with complex background

More Information

Received Date: July 12, 2010
Revised Date: October 11, 2010
Published Date: February 27, 2011

Graphical Abstract

Abstract

Abstract

A new segmentation method of the level set model based on prior information was proposed in this paper and was applied to crop diseased leaves with complex background. Firstly, structure tensor information was used to improve the LBF model, so that a new level set model was constructed with structure tensor information. At he same time, target shape was represent by the level set method. Secondly, prior shape information in the form of energy function was introduced to the new level set model and got the new level set model based on prior information. Finally, cucumber disease leaf images with complex background were segmented by the model. Experimental results show that the method can accurately extract the disease leaf from cucumber disease leaf images with complex background, which can provide the foundation for extracting, identifying and diagnosing the diseased spots.
- image segmentation,
- level set method,
- structure tensor,
- prior shape,
- complex background

FullText(HTML)

References (0)

[1]	XIANG Yuyun, CHEN Siyuan, GAO Shuang, LI Shuqin. Crop disease identification method based on adaptive BayesShrink and frequency-spatial feature fusion[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2025, 41(6): 204-215. DOI: 10.11975/j.issn.1002-6819.202410109
[2]	Zheng Jianhua, Yang Gaolin, Liu Shuangyin, Cao Liang, Zhang Zihao. Accurate estimation of underwater image restorationbased on dual-background light adaptive fusion and transmission maps[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2022, 38(14): 174-182. DOI: 10.11975/j.issn.1002-6819.2022.14.020
[3]	Sun Jun, Zhu Weidong, Luo Yuanqiu, Shen Jifeng, Chen Yide, Zhou Xin. Recognizing the diseases of crop leaves in fields using improved Mobilenet-V2[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(22): 161-169. DOI: 10.11975/j.issn.1002-6819.2021.22.018
[4]	Hu Gensheng, Wu Jitian, Bao Wenxia, Zeng Weihui. Detection of Ectropis oblique in complex background images using improved YOLOv5[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(21): 191-198. DOI: 10.11975/j.issn.1002-6819.2021.21.022
[5]	Liu Libo, Cheng Xiaolong, Dai Jianguo, Lai Junchen. Adaptive threshold segmentation for cotton canopy image in complex background based on logistic regression algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(12): 201-208. DOI: 10.11975/j.issn.1002-6819.2017.12.026
[6]	Wang Yude, Zhang Xuezhi. Segmentation algorithm of muskmelon fruit with complex background[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(2): 176-181. DOI: 10.3969/j.issn.1002-6819.2014.02.023
[7]	Diao Zhihua, Wang Huan, Song Yinmao, Wang Yunpeng. Segmentation method for cotton mite disease image under complex background[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2013, 29(5): 147-152.
[8]	Jiang Haiyang, Zhang Jian, Yuan Yuan, He Miantao, Zheng Shouguo. Segmentation of cucumber disease leaf image based on MDMP-LSM[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012, 28(21): 142-148.
[9]	Lü Yongchun, Ma Qin, Li Shaoming, Zhu Dehai, Zhang Xiaodong, Yang Jianyu, Liu Zh, Wang Hu, He Haocheng. Image features measurement of maize ear based on background plate scale[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(14): 43-47.
[10]	Li Jiangbo, Rao Xiuqin, Ying Yibin, Ma Benxue, Guo Junxian. Background and external defects segmentation of navel orange based on mask and edge gray value compensation algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2009, 25(12): 133-137.