Banana Leaf Disease Detection Using Image Processing Methods

Lim, Roy Soo Koon (2020) Banana Leaf Disease Detection Using Image Processing Methods. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

This paper presents a detection and classification of banana leaf disease in image processing. One of the most popular fruit which is banana and it produce by 130 tropical and subtropical country over 100 million ton annually. It is affected by various disease out of which Sigatoka are major importance. Sigatoka disease is a three disease in one it is a three-fungus disease complex, it has already reduced banana yield by 40%. Its three fungal disease which are Yellow Sigatoka (Pseudocercospora musae), Eumusae leaf spot (Pseudocercospora eumusae) and Black Sigatoka (Pseudocercospora figiensis). When farmer trying to control the Sigatoka disease, there is being threatened by a new disease called fusarium oxysporum, it is the soil-borne fungus. By developing a banana leaf disease detection system use the advance computer technology such as image processing to support and help the farmer to identify the disease at an initial or early stage and this project can provide a good and useful information to control the disease. Therefore, the present study was implemented on detect the disease on banana leaf by using the image processing. In project, the image processing process includes image acquisition, image pre-processing, image segmentation, feature extraction and classification and etc.