Oil Palm Fruit Bunches Grading System - Sim, Shiang Wei (Universiti Malaysia Sarawak, (UNIMAS), 2015)
Grading of oil palm fruit bunches manually may subjected to mistake and human error while examining the right category of the fruit bunches for the purpose of oil palm production in the oil palm mill. Hence, it is important to identify and classify the quality of the oil palm . fruit bunches. Image processing technique is implemented into the oil palm fruit bunches grading system. The grading system developed manage to distinguish between the four different categories of oil palm fruit bunches which are including unripe, under ripe, ripe and over ripe. The methodology consists of six stages which are including image acquisition, image pre-processing, color processing, image segmentation, classification, and results and evaluation. The saturation element in the HSV model was selected as the parameter for the threshold value. The ripeness of the oil palm fruit bunch could be differentiated between the different categories of fruit bunches based on the percentage of the ripeness areas masked on the surface of the fruit. The fruit classification ability of the prototype system yields above 85% accuracy from the experiment results achieved. By implementing the image processing technique into the grading system can help to increase the efficiency and quality of grading the fruit bunches for oil palm mill.