This thesis presents a system for detecting the colour and orientation of a cube using computer vision in a combination with a robotic system. Such systems are called machine vision systems, which allow us to automatically detect components help us and to assemble them efficiently and accurately.
The first part of the thesis introduction to machine vision, colour image detection and processing, and robotics. Machine vision describes how machine vision works and the most commonly used detection methods. Then, the operation of the sensor used in a machine vision is presented. Machine vision other physical elements are also presented: image detection, such as lens, aperture and exposure, and get a better understanding of the colour detection system in a digital image. The second part describes the hardware and software from Dobot that was used in my thesis. The kit contains the robot, camera, lighting source, installation equipment and two programs. In the software part, we first perform the calibration procedure, then we build the program to run the system. The system works by first capturing the image and processing it, then the robot serves the cubes. The thesis concludes with a discussion of the system's performance, such as colour detection accuracy, robot repeatability and its suitability in automated processes.
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