AI Article Synopsis
- The line-scanning stereo vision system offers high optical accuracy, efficient data transmission, and a broad field of vision, making it ideal for industrial product inspections.
- However, the one-dimensional nature of line-scanning cameras leads to motion distortion, which negatively impacts detection accuracy.
- To address this, a binocular color line-scanning stereo vision system was developed, utilizing a checkerboard target and a cubature Kalman filter to correct motion distortion, resulting in a 57.3% improvement in image data accuracy.
Article Abstract
Thanks to the line-scanning camera, the measurement method based on line-scanning stereo vision has high optical accuracy, data transmission efficiency, and a wide field of vision. It is more suitable for continuous operation and high-speed transmission of industrial product detection sites. However, the one-dimensional imaging characteristics of the line-scanning camera cause motion distortion during image data acquisition, which directly affects the accuracy of detection. Effectively reducing the influence of motion distortion is the primary problem to ensure detection accuracy. To obtain the two-dimensional color image and three-dimensional contour data of the heavy rail surface at the same time, a binocular color line-scanning stereo vision system is designed to collect the heavy rail surface data combined with the bright field illumination of the symmetrical linear light source. Aiming at the image motion distortion caused by system installation error and collaborative acquisition frame rate mismatch, this paper uses the checkerboard target and two-step cubature Kalman filter algorithm to solve the nonlinear parameters in the motion distortion model, estimate the real motion, and correct the image information. The experiments show that the accuracy of the data contained in the image is improved by 57.3% after correction.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11204702 | PMC |
| http://dx.doi.org/10.3390/jimaging10060144 | DOI Listing |
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