Volume : II, Issue : XII, December - 2013

Estimation of Yellow Rust in Wheat Crop Using K–Means Segmentation

Amina Bhaika

Abstract :

The presented work describes a software prototype system for yellow rust disease detection based on the infected images of various wheat plants. Images of the infected wheat plants are captured by closed circuit CCD cameras to cover approximately 3 sq. meter area that could acquire good quality images of wheat crop and processed for getting a gray colored image and then using image growing, image segmentation techniques to detect infected parts of the plants. Then the image is transferred to the analysis algorithm to report the quality. The methods evolved in this system are both image processing and soft computing techniques applied on a number of diseased wheat plant images. The wheat images are acquired by using a CCD camera of approx. 3 M-Pixel resolution in 24-bits color resolution. The images are then transferred to a PC and represented in MATLAB software. The RGB image is then segmented using K-means algorithm for segmentation of yellow rust in the wheat crop. The segmented yellow rust part is now analyzed for its percentage presence..

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Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Amina Bhaika Estimation of Yellow Rust in Wheat Crop Using K-Means Segmentation International Journal of Scientific Research, Vol.II, Issue.XII December 2013

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