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Separation of abnormal regions on black gram leaves using image analysis
Author(s)
Noinongyao, Pavit
Watchareeruetai, Ukrit
Khantiviriya, Puriwat
Wattanapaiboonsuk, Chaiwat
Duangsrisai, Sutsawat
Date Issued
September 5, 2017
Type
Conference Paper
Abstract
This paper proposes an image analysis method for separating abnormal regions caused by nutrient deficiencies on plants' leaves. The proposed method analyzes a histogram of normal leaves' colors to identify abnormalities on leaves. It can be divided into three main steps. Firstly, color features of leaf region in an input image are computed. Secondly, for each pixel, its color features are compared to the corresponding bin in the histogram to determine whether the pixel is abnormal. Finally, a post-processing technique is then applied to reduce noises in the result. Experiments have been conducted using black gram (Vigna mungo) leaves with five different nutrient deficiencies. The experimental results show that the proposed method can separate abnormal regions with an accuracy of above 90%.
Citation
Proceedings of the 2017 14th International Joint Conference on Computer Science and Software Engineering Jcsse 2017, 2017