A Real-Time Object Counting and Collecting Device for Industrial Automation Process using Machine Vision
Authors :- Kamlesh Kumar, Prince Kumar, Varsha Kshirsagar, Raghavendra Bhalerao, Krupa Shah, Pulin Vaidhya and Sampad Panda
Publication :- IEEE Sensors Journal,
An efficient product packing system through a simplified automatic counting and collecting process is a critical aspect of the manufacturing industry. In the present paper, we propose a real-time tool for simultaneous counting and collection of the objects into different bins using machine vision. The system employs a minimum distance classifier for object detection, Counting on the conveyor belt is done by tracking the Euclidian distances between the centroids of the objects in successive frames. Furthermore, the required number of object collection is carried out in two steps. In the first step, multiple objects nearest to the required count are collected. In the second step, the difference of objects that remained from the previous step are added one by one. Object collection is carried out by integrating software output to the hardware, which collects them in required numbers in the different bins. To meet the fast counting requirements, a high-speed conveyor system constituting vision sensor with pixel resolution of 1920x1200 and 41 frames per second frame rate is employed. The high computational power requirements for implementing the algorithm is accomplished by employing a dedicated graphics microcontroller, whose GPIO pins are used for interfacing the hardware for the object collection. The testing results of the proposed device with 30 variants of different plumbing industry objects confirm an accuracy of 100% for a period of 3 hours. Moreover, the proposed module is scalable and could boost the productivity of the company in a complex environment without affecting the accuracy of the system.