Support Vector Machine-based Detection of Pak Choy Leaves Conditions Using RGB and HIS Features

Ade Ramdan, Bambang Sugiarto, P. Dicky Rianto, Esa Prakasa, Hilman F. Pardede

Abstract: Vegetables are good sources to meet the needs for protein, vitamins, minerals for human. One of popular choices for vegetables in Indonesia is Pak Choy (Bassica rapa). Good quality vegetables is usually identified by the color and the shape of the leaves. Therefore an automatic system to detect the quality of the leaves is needed. In this paper, we propose a proper method to detect the quality of the Pak Choy leaves using machine learning. Monitoring the quality of Pak Choy leaves with the naked eye is usually conducted based on the color of the leaves. The healthy leaves are usually characterized by green color while the unhealthy leaves are usually have a green color with the yellow spot. Based on these observations, we develop the system using color intensity features such as RGB and HSI and Support Vector Machine (SVM) as the classifiers. Our system achieves accuracy of 92.5% using linear kernels.