Color Distribution Analysis for Ripeness Prediction of Golden Apollo Melon

Abstract

Human visual perception on color of melon fruit for ripeness judgement is a complex phenomenon that depends on many factors, making the judgement is often inaccurate and inconsistent. The objective of this study is to develop an image processing algorithm that can be used for distinguishing ripe melons from unripe ones based on their skin color. The image processing algorithm could then be used as a pre-harvest tool to facilitate farmers with enough information for making decisions about whether or not the melon is ready to harvest. Four sample groups of Golden Apollo melon were harvested at four different age, with 55 fruits in each group. Using the color distribution as results of the image analysis, the first two groups of the samples can be separated from other groups with minimal overlap, but they cannot be separated in the other two groups. The color image analysis of the melons in combination with discriminant analysis could be used to distiguish between harvesting age groups with an average accuracy of 86%.