KEYWORDS: Feature extraction, Structured light, 3D modeling, Image processing, 3D acquisition, Environmental sensing, 3D vision, Visual process modeling, Inspection, 3D image processing
Robot 3D vision inspection plays a very important role in intelligent manufacturing process such as automated picking, obstacle avoidance, path planning and so on. Recently, there is a need for a fast detection method that has applicability to complex environments, strong anti-interference capabilities, and balances speed and accuracy to meet the above requirements. An environment feature detection method based on laser-assisted machine vision is proposed. By illuminating the grid structure to the target scene, the binocular camera is used to collect the grid image on the surface of the target scene. Then A two-step feature extraction method is proposed, which is locating the feature position quickly first, and then accurately obtaining the coordinate of the feature point. Firstly, an improved fast extraction method is proposed to realize the fast recognition of feature points. Secondly, in the aspect of accurate acquisition, a new improved steger fitting method is proposed to accurately extract the position of feature points. Finally, fast matching and reconstruction of the exact position of feature points on the two images collected by binocular camera are implemented to achieve fast and high precision 3D detection. This experiment has verified the rationality of the system scheme, the correctness, the precision and effectiveness of the relevant methods.
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