Indonesian Journal of Electrical Engineering and Computer Science
Vol 11, No 6: June 2013

Cotton Pests and Diseases Detection Based on Image Processing

Qinghai He (Shihezi University)
Benxue Ma (Shihezi University)
Duanyang Qu (Shihezi University)
Qiang Zhang (Shihezi University)
Xinmin Hou (University of the Broadcast and Television in Xinjiang)
Jing Zhao (Shandong University of Technology)



Article Info

Publish Date
01 Jun 2013

Abstract

Extract the damaged image form the cotton image in order to measure the damage ratio of the cotton leaf which caused by the diseases or pests. Several algorithms like image enhancement, image filtering which suit for cotton leaf processing were explored in this paper. Three different color models for extracting the damaged image from cotton leaf images were implemented, namely RGB color model, HSI color model, and YCbCr color model. The ratio of damage (γ) was chosen as feature to measure  the degree of damage which caused by diseases or pests. This paper also shows the comparison of the results obtained by the implementing in different color models, the comparison of results shows good accuracy in both color models and YCbCr color space is considered as the best color model for extracting the damaged image. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2721

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