Color-Based Automated Sorting System Using Image Processing Techniques

Abstract

Automatic object sorting system is a technology developed to meet the needs of industries that want to increase production efficiency, reduce human errors, and save time in the production process. The use of robots and various detection technologies such as image processing and artificial intelligence (AI) to help sort objects accurately. This thesis aims to study the image processing detection system, test the PLC used in conjunction with image processing in color sorting, and find the efficiency of the color sorting simulation set on the automatic conveyor system. This research designed a system that can sort objects of different colors according to the set values, with 3 levels of belt speed adjustment (slow, medium, fast) using a camera to detect the color of the object and a solenoid to separate objects that match the properties. Testing was conducted to measure the accuracy and efficiency of the system. The results of the research found that the developed system can sort objects according to the set color. It can also work continuously and adjust the speed without losing efficiency. This project was successful in developing a highly accurate automatic object sorting system that can be used in many industries, such as food production, agriculture, and electronic parts production. This system helps reduce costs, increases production efficiency, and is a potential training tool to develop knowledge in automation systems in the future accurately.