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Proceedings Paper

Crop extraction based on ultra-simple neural network modeling in the normalized rgb and CIE L*a*b* color spaces
Author(s): Lei Hu; Xiaodong Bai; Aiping Yang; Kun Zhang; Chonghua Zhang; Bo Liu
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Paper Abstract

Crop extraction from the images captured in the field is a complex task. In this paper, a new crop segmentation method is presented based on a designed lightweight neural network which only has 5-layer. In the proposed method, the lightweight neural network is designed and constructed to deal with the crop color features in the normalized RGB and CIE L*a*b* color spaces to realized the accurate segmentation of crop images. To verify the performance of the proposed method, 120 rice images are utilized to compare the proposed method with four other famous approaches. Experiment demonstrates that our method is robust to the illumination variations in the field and performed better than other approaches. Experiment shows our method can be used to the task of crop segmentation accurately and efficiently.

Paper Details

Date Published: 14 February 2020
PDF: 8 pages
Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114301V (14 February 2020); doi: 10.1117/12.2541856
Show Author Affiliations
Lei Hu, Nanchang Agricultural Meteorological Key Lab. (China)
Xiaodong Bai, Nanjing Univ. of Posts and Telecommunications (China)
Aiping Yang, Agricultural Meteorological Ctr. of Jiangxi Meteorological Bureau (China)
Kun Zhang, Agricultural Meteorological Ctr. of Jiangxi Meteorological Bureau (China)
Chonghua Zhang, Nanchang Agricultural Meteorological Key Lab. (China)
Bo Liu, Nanjing Univ. of Posts and Telecommunications (China)


Published in SPIE Proceedings Vol. 11430:
MIPPR 2019: Pattern Recognition and Computer Vision
Nong Sang; Jayaram K. Udupa; Yuehuan Wang; Zhenbing Liu, Editor(s)

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