Beihang University

Junhua Sun

Guangjun Zhang

Zhenzhong Wei

Zhen Liu

Qianzhe Liu

Meng Xie

Fuqiang Zhou

Qingbo Li

The present disclosure provides a global calibration method based on a rigid bar for a multi-sensor vision measurement system, comprising: step 1, executing the following procedure for at least nine times: placing, in front of two vision sensors to be calibrated, a rigid bar fasten with two targets respectively corresponding to the vision sensors; capturing images of the respective targets by their corresponding vision sensors; extracting coordinates of feature points of the respective targets in their corresponding images; and computing 3D coordinates of each feature points of the respective targets under their corresponding vision sensor coordinate frames; and Step 2, computing the transformation matrix between the two vision sensors, with the constraint of the fixed position relationship between the two targets. The present disclosure also provides a global calibration apparatus based on a rigid bar for a multi-sensor vision measurement system. Putting the present disclosure to use can increase the accuracy of the global calibration, and also be suitable for the calibration of the multi-sensor vision system in the extremely large working space, which enlarges the application range of the present disclosure.

Global calibration method with apparatus based on rigid bar for multi-sensor vision

This disclosure provides a calibration method for structure parameters of a structured-light vision sensor, which includes setting up the coordinate frames of a camera, image plane and target for calibration. The calculation of coordinates in the camera coordinate frame of stripes, projected by structured-light, on the planar target and a structured-light equation fitting according to the coordinates in the camera coordinate frame of the stripes on the planar target, by moving the planar target arbitrarily multiple times. The calibration method of the structured-light vision sensor provided by the disclosure is easy to operate and no auxiliary apparatus is needed, which can not only promote the efficiency of the calibration of structured-light, but also extend the application scope of calibration of structured-light.

Calibration method for structure parameters of structured-light vision sensor

The invention discloses a vehicle dynamic measurement device for comprehensive parameters of rail wear, which comprises a vision sensor, a computer and a milometer. A high-speed image acquisition card and a measurement module are installed in the computer. The vision sensor comprises imaging system for rail cross-section and a raster projector which can project more than one light plane perpendicular to the measured rail. The measurement module is used for calculating vertical wear, horizontal wear, the amplitude and wavelength of corrugation wear. The invention also discloses a vehicle dynamic measurement method for comprehensive parameters of rail wear. The invention can increase the sampling rate of image sensing and acquisition hardware equipment with no need of improving the performance of it, thereby satisfy high-speed on-line dynamic measurement requirements for corrugation wear, and the amplitude and wavelength of corrugation wear can be calculated more precisely.

Vehicle dynamic measurement device and method for comprehensive parameters of rail wear

The present disclosure is directed to a three-dimensional data registration method for vision measurement in flow style based on a double-sided target. An embodiment of the disclosed method that comprises A. Setting up two digital cameras which can observe the entire measured object; B. Calibrating intrinsic parameters and a transformation between the two digital camera coordinate frames; C. A double-sided target being placed near the measured area of the measured object, the two digital cameras and a vision sensor taking images of at least three non-collinear feature points of the double-sided target; D. Removing the target, measuring the measured area by using the vision sensor; E. Respectively computing the three dimensional coordinates of the feature points in the global coordinate frame and in the vision sensor coordinate frame; F. Estimating the transformation from the vision sensor coordinate frame to the global coordinate frame through the three dimensional coordinates of the three or more non-collinear feature points obtained at step E, then transforming the three dimensional data of the measured area to the global coordinate frame; and G. Repeating step C, D, E, F, then completing three dimensional data registration for all measured areas. The present disclosure improves three dimensional data registration precision and efficiency.

Growing community of inventors

Beijing, China

Junhua Sun