Abstract
In binocular vision inspection system, the calibration of detection equipment is the basis to ensure the subsequent detection accuracy. The current calibration methods have the disadvantages of complex calculation, low precision, and poor operability. In order to solve the above problems, the calibration method of binocular camera, the correction method of lens distortion, and the calibration method of projector in the binocular vision system based on surface structured light are studied in this paper. For lens distortion correction, on the basis of analyzing the traditional correction methods, a distortion correction method based on radial basis function neural network is proposed. Using the excellent nonlinear mapping ability of RBF neural network, the distortion correction models of different lenses can be obtained quickly. It overcomes the defect that the traditional correction model cannot adjust adaptively with the type of lens. The experimental results show that the accuracy of the method can meet the requirements of system calibration.
Highlights
With the development of modern electronic technology, the application of 3D detection in the machining field is more and more mature
In the traditional reverse engineering, the common method of 3D object detection is the contact measurement technology represented by coordinate measuring machine (CMM). e advantage of this method is that it is easy to operate
The above conditions are generally difficult to meet. erefore, a binocular vision system composed of one projector and two cameras is usually used for 3D reconstruction [5, 6]
Summary
With the development of modern electronic technology, the application of 3D detection in the machining field is more and more mature. Structured light detection is a representative method of noncontact measurement technology [2]. The projector projects structured light with specific rules to the target surface. E distorted structured light image contains the depth information of the measured target surface and the relative position of the projector and camera. In the process of calculation, in order to determine the relationship between the 3D geometric position of a point on the surface of a space object and its corresponding point in the image, it is necessary to establish the geometric model of the camera and projector. E parameters of these geometric models are the parameters of the camera and projector, including internal parameters, external parameters, and distortion parameters In most cases, these parameters can only be obtained by experiment and calculation. Security and Communication Networks measurement and calculation [3,4,5]. erefore, it is very important to study the high-precision and high-efficiency system calibration method for the 3D detection system
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