Maize Disease Detection using Color Cooccurrence Features

The Ethiopian economy is based primarily on agriculture. Furthermore, due to Ethiopia's predominately agricultural economy, most Ethiopians are dependent agriculture in some way. In Ethiopia, traditional dishes including bread, injera, and soup commonly made from one of the plants, maize. Although growing maize, Wollo farmers experience low levels yield a variety problems. This study examines features color co-occurrence identify Maize illness. it has not been proven, several diseases may occur Ethiopia. this research images retrieved, while texture feature matrix used. Artificial Neural Networks Leaf Color Analysis used categorize classified as Blast, Brown Spot, Narrow Normal Leaf. Analyze classify disease, process entails acquiring, evaluating, classifying images. entire sample goes through leaf analysis before moving artificial neural network.. All samples subjected throughout testing step order diseases. If sample's RGB values fall within predetermined range, automatically normal leaf; nevertheless, all diseased undergo image processing get that utilized train evaluate an network. generated model then discovered when network trained using these features. As result, technique with accuracy rate roughly 86%.