Paper
6 November 2023 Data fusion of line structured light and photometric stereo point clouds based on wavelet transformation
Jingbo Zhou, Jianxin Shi, Yuehua Li, Xiaohong Liu, Wenhao Yao
Author Affiliations +
Proceedings Volume 12921, Third International Computing Imaging Conference (CITA 2023); 129213A (2023) https://doi.org/10.1117/12.2691547
Event: Third International Computing Imaging Conference (CITA 2023), 2023, Sydney, Australia
Abstract
Achieving high accuracy and fine-grained three-dimensional (3D) results has been an important research direction in visual measurement. Line Structured Light Sensor (LSLS) has the advantage of high accuracy but lacks clarity. Conversely, Photometric Stereo (PS) provides higher clarity but lower measurement accuracy. To address this issue, a novel method is proposed which fuses the point clouds from both LSLS and PS by use of two-dimensional wavelet transformation. The object is firstly measured by use of the LSLS and PS methods separately to obtain point cloud data. The surface points are then matched, and the measurement results are decomposed using wavelet transformation. The corresponding low-frequency and high-frequency information can be obtained. Subsequently, the low-frequency information from LSLS and the high-frequency information from PS, at suitable scales, are selected for reconstruction. Fused result through this process ensures high measurement accuracy and clarity. Experiments also validate the effectiveness of this method.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jingbo Zhou, Jianxin Shi, Yuehua Li, Xiaohong Liu, and Wenhao Yao "Data fusion of line structured light and photometric stereo point clouds based on wavelet transformation", Proc. SPIE 12921, Third International Computing Imaging Conference (CITA 2023), 129213A (6 November 2023); https://doi.org/10.1117/12.2691547
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KEYWORDS
Data fusion

Structured light

3D metrology

Point clouds

Information fusion

Wavelet transforms

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