Modeling of Oil Palm Fruit Maturity for the Development of an Outdoor Vision System

Abstract

Color is the most important indicator farmers use to determine the maturity of the oil palm fruit called fresh fruit bunches (FFB) in the manual harvesting process. To automate the harvesting operation, the development of a vision system will replace the human eye for mature FFB recognition. In real plantation environments, variations in the daylight caused the light intensity to change, thus becoming the main issue that affects the automatic recognition process. In this study, the matured FFB was captured using a Sony digital Handycam on the day shift period. At the same time period of daylight intensity, a unit on foot candles (FC) also was simultaneously recorded using an Extech lightmeter data logger. From the linear regression analysis process, the mathematical model shows that there is a linear change between daylight intensity with the pixel value of the components green and blue. For the pixel value of the red component, the value will be linear at a maximum of 255 and at a certain intensity. To validate the mathematical model, this equation is used in the development of software for outdoor recognition processes.