Image Reduction Method for Rice Leaf Disease Based on Visual Attention Model

Li Bo Liu; Chun Jiang Zhao; Hua Rui Wu; Rong Hua Gao

doi:10.4028/www.scientific.net/AMM.220-223.1393

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 220-223Image Reduction Method for Rice Leaf Disease Based...

Image Reduction Method for Rice Leaf Disease Based on Visual Attention Model

Abstract:

Analyzing the crop growth status through leaf disease image is one of the hottest issues in agriculture and forestry fields currently. But the size of image gathered by digital camera is too large, the focus of this research is to zooming-out image at the condition of ensuring the main information which carried by the image to distort lower. Based on the further study of visual attention model proposed by Itti and Ma YF. This paper establishes visual attention and visual saliency map of rice blast and brown spot disease image, whose size is 4272*2878 pixels. Finally, determines the reduction scale of the corresponding effective target collection and provide a new way to reduce the plant leaf images.

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Periodical:

Applied Mechanics and Materials (Volumes 220-223)

Pages:

1393-1397

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.220-223.1393

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Online since:

November 2012

Authors:

Li Bo Liu, Chun Jiang Zhao, Hua Rui Wu, Rong Hua Gao

Keywords:

Image Reduction, Rice Leaf, Visual Attention Model

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References

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