Objective As an advanced measurement tool, 3D reconstruction technology has demonstrated significant application advantages in a number of key areas such as biomedicine, aerospace, and industrial manufacturing due to its unique non-contact nature, efficient data processing capability, and ability to provide in-depth multi-dimensional analysis. However, as the application of the technology continues, the existing light bar extraction methods face the dual challenges of slow reconstruction speed and large accuracy errors when dealing with objects with complex geometries and under variable environmental noise conditions. These challenges not only affect the accuracy of 3D reconstruction results, but also constrain the efficiency of data processing, limiting the potential application of 3D scanning technology in a wider range of scenarios. In order to overcome the limitations of existing techniques and enhance the overall performance of 3D scanning technology, proposes an efficient light bar extraction method based on 3D reconstruction (ELE-3D). The ELE-3D method is developed with the goal of achieving a significant speed-up of the light bar extraction process, while at the same time guaranteeing or even improving the accuracy and reliability of the 3D reconstruction. Specifically, the ELE-3D method aims to accurately extract the centerline of the light bar through advanced image processing techniques and methodic optimisation, effectively reduce noise interference and increase data processing speed.
Methods The ELE-3D method is optimized for its limitations in dealing with complex-shaped objects and noise interference through an in-depth analysis of the shortcomings of existing light strip extraction techniques. The method first uses the Sobel operator to perform edge enhancement to improve the contrast and clarity of the edges. Subsequently, binarization is performed based on the maximum gray value of the image to effectively separate the laser stripes from the background noise. Noise filters with area and aspect ratio thresholds are then applied to refine the extraction process, ensuring that only the most relevant features are preserved. It adjusts the laser strip projection ratio to significantly reduce computational demands. Finally, the ELE-3D method adopts a sub-pixel technique for accurate centerline extraction of the segmented region (Fig.1).
Results and Discussions In the comprehensive experimental analysis of the ELE-3D method, first compare the extraction speed and effect of the ELE-3D method with the traditional Gray-gravity method and Steger method in light bar centerline extraction by efficiency test, which shows that the ELE-3D method significantly outperforms the other two methods by an average time consuming of 64.2 ms, demonstrating excellent extraction speed and stability. (Fig.2-3, Tab.1-2). Then, in the robustness validation experiment, we added Gaussian noise of different intensities to the standard image, and the ELE-3D method can maintain high accuracy in centerline extraction even in a high noise environment, showing stronger anti-interference ability compared with the traditional methods (Fig.4). Finally, in the 3D reconstruction accuracy experiments, the ELE-3D method scanned a standard ball, a doll and a mannequin from multiple viewpoints, and the complex shapes and details were clearly captured by the generated point cloud data, which verified the validity and reliability of the ELE-3D method in practical applications (Fig.5-7, Tab.3-4). Taken together, these experimental results show that the ELE-3D method performs well in terms of efficiency, robustness and accuracy, providing solid technical support for the advancement of 3D scanning technology.
Conclusions The experimental results show that the ELE-3D method has improved the light bar extraction speed by 89.0% compared to the traditional Steger method and by 85.3% compared to the Gray-gravity method, and the running time is stable, showing high efficiency and stability. In terms of robustness, the ELE-3D method can maintain high extraction accuracy under different noise levels, showing good anti-noise performance. Through the multi-view point cloud 3D reconstruction experiments, the ELE-3D method is able to capture rich details on different test objects, such as standard balls, dolls, and mannequins, which proves its high efficiency and accuracy in scanning complex shapes and surfaces. These results not only prove the feasibility of the ELE-3D method, but also lay the foundation for future applications in a wider range of fields, which indicates that the ELE-3D method has a broad application prospect in the field of 3D scanning.
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