An Automatic Coffee Plant Diseases Identification Using Hybrid Approaches of Image Processing and Decision Tree

Abrham Debasu Mengistu (Bahir Dar Institute of Technology)
Seffi Gebeyehu Mengistu (Bahir Dar University)
Dagnachew Melesew Alemayehu (Bahir Dar University)

Indonesian Journal of Electrical Engineering and Computer Science
Vol 9, No 3: March 2018

Coffee Leaf Rust (CLR), Coffee Berry Disease (CBD) and Coffee Wilt Disease (CWD) are the three main diseases that attack coffee plants. This paper presents the identification of these types diseases using hybrid approaches of image processing and decision tree. The images are taken from Southern Ethiopia, Jimma and Zegie. In this paper backpropagation artificial neural network (BPNN) and decision tree had been used as techniques; a total of 9100 images were collected. From these, 70% are used for training and the remaining 30% are used for testing. In general, 94.5% accuracy achieved when decision tree and BPNN with tanh activation function are combined.