Ball detection process tracking using digital image processing concepts with the help of python software tool utilzing an autonomous 2-DOF mobile robot

Abstract

The ‘Ball Detection and Tracking through Image Processing using Python’ project is a cutting-edge endeavor with the goal of real-time ball identification and tracking through advanced computer vision methodologies. This initiative employs a camera to capture live video footage of the ball, which is subsequently processed using the Python OpenCV library. The project can be broken down into two pivotal phases: ball detection and ball tracking. In the initial phase, the algorithm adeptly identifies the ball within the video frame by recognizing its characteristic circular shape. Following this, the second phase delves into the meticulous tracking of the ball's movement through the implementation of optical flow techniques. Remarkably, this software is versatile and compatible, designed to operate seamlessly on both Raspberry Pi and standard PCs, enabling real-time video processing.  The software yields a tangible output in the form of the ball's precise position, which is prominently displayed on the screen. This positional data can be harnessed for a multitude of applications, such as steering robotic systems to follow the ball's trajectory. The project's utility transcends boundaries, finding relevance in diverse fields like sports analytics, where it can be employed to track ball movements in sports like football or basketball. Additionally, it is invaluable in industrial automation, where it can efficiently track the motion of objects on conveyor belts. In essence, the ‘Ball Detection and Tracking through Image Processing using Python’ project stands as a remarkable illustration of computer vision's real-time video processing capabilities. Its potential to revolutionize industries and usher in novel opportunities for automation and data analytics is truly compelling.