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Proceedings Paper

The edge extraction of agricultural crop leaf
Author(s): Beilei Wang; Ying Cao; Huiming Xiao; Huiyan Jiang; Hongjuan Liu
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Paper Abstract

In agricultural engineering, to ensure rational use of pesticide and improvement of crop production, computer image recognition technology is currently applied to help farmers to identify the degree of crop diseases. Considering the importance of feature extraction in this field, in this paper, we first present and discuss several widely used edge operator, including Sobel, Prewitt, Roberts, Canny and LoG. Furthermore, an experiment is conducted to compare performance and accuracy of five operators by applying them to a leaf image taken from agricultural crop for edge detection. The results of experiment show that, in practice, LoG edge operator is relatively a better choice and performs well for edge detection of agricultural crop leaf image.

Paper Details

Date Published: 10 July 2009
PDF: 7 pages
Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 748916 (10 July 2009); doi: 10.1117/12.836721
Show Author Affiliations
Beilei Wang, Northeastern Univ. (China)
Ying Cao, Northeastern Univ. (China)
Huiming Xiao, Northeastern Univ. (China)
Huiyan Jiang, Northeastern Univ. (China)
Hongjuan Liu, Northeastern 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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