DEVELOPING DESIGN OF AUTOMATIC EGG QUALITY DETECTOR USING ROI AND RGB TEMPLATE METHODS - Herlambang, Teguh; Suryowinoto, Andy; Zakaria, Moch; Tomasouw, Berny Pebo (PATTIMURA UNIVERSITY, 2022)
The eggs of purebred chickens always become the major choice for satisfying people’s needs for nutrients. The way to process them is easy, and the prices are relatively cheap for all people. Since the eggs of purebred chickens are in high demand, a device that can detect their qualities more correctly and accurately is needed, compared to the conventional method. Objective: An automatic egg quality detector was developed through a camera module of pixy cmucam5 by employing ROI and template RGB methods. The implementation of the ROI method could optimize the system performance, thereby accelerating the process of egg quality detection carried out by the preprocessor of the pixy camera. ROI analyzed the egg image only on the desired pixel area, not the whole pixel. As a result, the ROI method yielded a device and system that could detect the egg quality within the average speed of detection time -/+ 2ms per egg out of 4 trial categories. Meanwhile, the template RGB method was able to improve and ease the ability of the pixy camera module in detecting the egg quality. When the RGB index of the egg was < 234, then the egg was of good quality. Contrarily, when the RGB index of the egg was > 234, the egg quality was in a bad category. The contribution of this paper is to develop a low-cost automatic egg sorting and detection system with the advantages of flexibility in device placement, due to the use of camera modules and object detection accuracy, as well as better response time than using color sensors. Accordingly, the template RGB method produced a device and system which could detect egg quality with average accuracy of 90 % and average error of 10% out of 4 trial categories. And, the results of the trials upon the detector system indicated success in detecting the egg quality.