Journal ArticleDOI
Computer vision based technique for identification and quantification of powdery mildew disease in cherry leaves
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TLDR
The experimental results indicate that proposed method for segmentation of powdery mildew disease affected area from leaf image of cherry crops is convincing and computationally cheap.Abstract:
There are different reasons like pests, weeds, and diseases which are responsible for the loss of crop production. Identification and detection of different plant diseases is a difficult task in a large crop field and it also requires an expert manpower. In this paper, the proposed method uses adaptive intensity based thresholding for automatic segmentation of powdery mildew disease which makes this method invariant to image quality and noise. After the segmentation of powdery mildew disease from leaf images, the affected area is quantified which makes this method efficient for grading the level of disease infection. The proposed method is tested on the comprehensive dataset of leaf images of cherry crops, which achieved good accuracy of 99%. The experimental results indicate that proposed method for segmentation of powdery mildew disease affected area from leaf image of cherry crops is convincing and computationally cheap.read more
Citations
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Detection of grapevine yellows symptoms in Vitis vinifera L. with artificial intelligence
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References
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Journal ArticleDOI
Review: A review of advanced techniques for detecting plant diseases
TL;DR: In this article, the authors present a review of the currently used technologies that can be used for developing a ground-based sensor system to assist in monitoring health and diseases in plants under field conditions.
Journal ArticleDOI
Pesticide productivity and food security. A review
TL;DR: In this article, the authors present a review of worldwide crop losses due to pests, estimates of pesticide-related productivity, and costs and benefits of pesticide use, approaches to reduce yield losses by chemical, as well as biological and recombinant methods of pest control and the challenges of the crop protection industry.
Journal ArticleDOI
Plant Disease Severity Estimated Visually, by Digital Photography and Image Analysis, and by Hyperspectral Imaging
TL;DR: This review considers plant disease severity assessment at the scale of individual plant parts or plants, and describes the current understanding of the sources and causes of assessment error, a better understanding of which is required before improvements can be targeted.
Proceedings ArticleDOI
Plant Disease Detection Using Image Processing
Sachin D. Khirade,A.B. Patil +1 more
TL;DR: The methods used for the detection of plant diseases using their leaves images are discussed and some segmentation and feature extraction algorithm used in the plant disease detection are discussed.
Journal ArticleDOI
An image-processing based algorithm to automatically identify plant disease visual symptoms.
Anyela Camargo,Jeremy S. Smith +1 more
TL;DR: An image-processing based method that identifies the visual symptoms of plant diseases, from an analysis of coloured images, showed that the developed algorithm was able to identify a diseased region even when that region was represented by a wide range of intensities.