Detection, Quantification and Analysis of Neofabraea Leaf Spot in Olive Plant using Image Processing Techniques

被引:0
|
作者
Sinha, Aditya [1 ]
Shekhawat, Rajveer Singh [1 ]
机构
[1] Manipal Univ Jaipur, Sch Comp & Informat Technol, Jaipur, Rajasthan, India
关键词
Image Processing; k-means; Olive; Plant disease; La*b*; Threshold; Leaf Spot; Neofabrea; SYMPTOMS; SEVERITY;
D O I
10.1109/ispcc48220.2019.8988316
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Plant diseases occur in various parts of plants and have a variety of identifying symptoms; the majority of them can be visually identified and evaluated. Barbedo [1] have thoroughly reviewed a variety of techniques used for detection, quantification and classification of plant diseases using image processing techniques. We have explored the plant diseases which are visually dominant and can be observed at the earlier stage of its life cycle. In this work, we have detected and quantified Neofabraea leaf spot in olive plants. The data has been collected from local olive farms and through online resources. We have isolated the Region of Interest(ROI) in the infected leaf using two different methodologies. Firstly we tried to apply thresholding technique on the Histogram values of the leaf image in the La*b* color model; we also have used the k-means based color segmentation on the RGB color model. Quantification of the disease is also performed using the ratio of the infected region by the whole area of the leaf and verified using visual identification.
引用
收藏
页码:348 / 353
页数:6
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