Real-time object detection and selection with the LabVIEW program

Nowadays, the demand for production is increasing due to the increase in the human population. For this reason, different developing technologies are used to meet the required production. In developing technologies, image processing techniques are used to save manpower and time and to minimize possible errors. In this study, image processing techniques were used to detect and select the colors and shapes of the objects coming over the conveyor belt system. Real-time images were preferred in the study. In the implemented system, the selection process was carried out by using the LabVIEW program to define the colors and shapes of the objects. LabVIEW NI- IMAQdx was used to find the colors of the objects. To facilitate the definition of shapes, the images taken from the Vision Assistant module in the LabVIEW program were converted to HSL format, and shape definitions were made using different algorithms. After these processes were done, the servo motors in the conveyor belt system were enabled to communicate with each other with the help of the Arduino program and the selection of the objects was carried out. According to the results obtained, the average accuracy rate for three-dimensional objects was 95.349 %. This rate is considered to be a very high rate for object detection of correct color and shape.