Novel Image Processing Technique for Feature Detection of Wheat Crops using Python OpenCV

Mamoon Rashid, Balwant Ram,Ranbir Singh Batth,Nazir Ahmad, Hatim M. Elhassan Ibrahim Dafallaa,Mohammed Burhanur Rehman

2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)(2019)

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Abstract
The job of this research is to filter the diseased part of the leaf from the leaf images. The authors proposed and implemented image processing technique using OpenCV for separating the diseased part of the leaf from the image of the leaf. Foreground Extraction, Edge Detection, Color filtering and Combination of Edge Detection with Color Filtering is done for wheat images.This novel technique can facilitate the process of the detection of diseases in wheat plants. The system allows to follow a particular pattern of capturing images of plants so that threats will be analysed quickly. Apart from helping humans to detect the diseases in plants, this research work can automate the process of detection without the need of human resources for feeding dataset to model, which is a much reliable process. This research will ultimately contribute in automation of agriculture processes faster and will make farmers to cultivate more in less amount of time.
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Key words
Image Processing,OpenCV 2,GrabCut,Canny Edge Detection,Pre Processing,Feature Extraction
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