Diseases detection of God’s plant - Aloe vera using image processing
Detection of diseases at the earliest will be an ultimate solution to improve the productivity of the plants aiming to raise the profit with minimum expenditure. Digital image processing techniques are efficiently used in agriculture for protecting the plants and crop management. In the conventional method the farmers used to get suggestions from agriculture officers on unknown diseases. Generally they are using naked eye observation method which is not an effective one. In this work we process the mobile captured images of aloe vera to detect the infected part of the plant for further processing. The system applies image processing techniques such as image acquisition, image pre-processing and edge detection to identify the diseases. The damage ratio will be calculated by extracting the disease affected aloe vera leaf. Three different color models for extracting the damaged image from aloe vera plant are implemented namely RGB, YCbCr and HSI and the results are compared. The experimental results show that the proposed approach enhances the accuracy of automatic detection of diseases in aloe vera using digital image processing.
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