International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 16, No. 4, 8 Aug. 2024
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Image Analysis of Impurity in Machine-harvested Cotton Based Machine Vision
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Author(s)
Mingjie LI
1,2,*
Vladimir Y. Mariano
1
Index Terms
Machine Vision, filtering, impurity, machine-harvested cotton
Abstract
The mechanization rate of cotton picking continues to increase with the continuous improvement and development of China's agricultural modernization level. However, when picking cotton, the machine cannot distinguish between cotton fibers and impurities well, resulting in a certain gap in impurity content compared to manually picked cotton. This paper combines machine vision and image processing technology to adopt an improved Canny-based impurity image processing algorithm. By performing light processing, selecting a color space, filtering images, and removing noise from machine-harvested cotton images, the suppression of virtual edges on impurity images allows for more accurate identification of impurities on the cotton surface. Finally, experimental details and results conclusively demonstrate the effectiveness of this method, providing a basis for detecting and classifying cotton impurities.
Cite This Paper
Mingjie LI, Vladimir Y. Mariano, "Image Analysis of Impurity in Machine-harvested Cotton Based Machine Vision", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.16, No.4, pp. 1-14, 2024. DOI:10.5815/ijigsp.2024.04.01
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