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AN INTENSITY INHOMOGENEITY SEGMENTATION BASED APPLE LEAF DISEASE DETECTION USING DEEP LEARNING


volume 5 issue 1 Download Paper
Year of Publication: 2019
Authors: Simranjeet kaur,Varun jasuja

Abstract


Apple tree is one of the most popular plants, which is mostly found in a hilly area. At the same time, Apple plants are among the most prone to diseases. Identifying the disease at an early stage and preventing it from spreading to other parts of the plant is a challenge for the expert. Therefore, it becomes necessary to design a system that can detect and identifies plant disease automatically. In this paper, an automatic apple leaf disease system is developed in MATLAB. The dataset for unhealthy as well as healthy leaves is collected from plant Village Dataset Master. A number of processes are performed on these leaves such as image enhancement, segmentation, features extraction and classification. At last, the parameters are measured to determine the efficiency of the proposed work. The test results demonstrated that the detection accuracy up to 99.34%.


References


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Keywords


Apple Plant Leaf, Apple scab, Apple Black rot, Apple Cedar, Apple Healthy, SURF, GA, CNN.