Evaluation of the quantization error in the convergence stereocameras

摘要

Computer vision techniques include the image acquisition, image processing and data analysis are currently popular and widespread. Stereo vision systems in the area of computer vision have been widely used in many applications, such as 3D depth reconstruction, 3D gaming, robot vision navigation, remote sensing, medical image processing, and so on. However, the high accurate 3D stereo vision scanners do not completely satisfy industry requirements due to the high price of these systems. In this paper, a novel method is proposed that increase the 3D measurement accuracy of stereo vision systems with low resolution and cheap cameras. This was achieved through discussing the quantization error of the 3D depth reconstruction of the stereo cameras. Accordingly, a mathematical model was introduced to evaluate the convergence stereo cameras quantization error. Meanwhile, a synthetic experiment was employed to validate our proposed mathematical model. Finally, the simulation experiments were conducted to demonstrate how to apply the presented approach to increase the accuracy measurement of the low resolution stereo vision cameras. The simulation results showed a considerable measurement improvement by changing the convergence angle of the stereo vision cameras.