Palm oil fresh fruit bunch ripeness grading identification using color features

Abstract

This research investigates the ripeness grading identification of the palm oil FFB using color features that are color histogram, color moment and color correlogram. Palm oil is harvested during the optimum stage of its ripeness since it improves the FFB oil quality and quantity. Harvesting wrong bunches decreases the oil extraction rate of the palm. A new dataset of images of FFB is A comparative study between Support Vector Machine (SVM) and Naïve Bayes constructed. A comparative study between Support Vector Machine (SVM) and Naïve Bayes classifiers has been performed using classifiers has been performed using the values of color histogram, color moment and color correlogram. The results of the experiments indicate that color moment with SVM produce a higher palm oil FFB ripeness grading identification accuracy compared to color histogram and color correlogram.