Parallelization Strategy of Laser Stripe Center Extraction for Structured Light Measurement

Abstract

Structured light, known for its high precision and noncontact advantages, is widely used in the fields of 3-D reconstruction and object measurement. The extraction of the light stripe center line has a significant impact on the high-precision measurement of structured light. However, traditional geometric approaches and gray centroid methods often struggle to reliably extract the stripe center, while Steger’s subpixel method is hindered by intensive computational demands, making real-time applications challenging. To address these limitations while ensuring the accuracy of laser stripe center extraction, we propose a parallelization strategy for the Steger algorithm, addressing the challenges associated with high-computational load. The proposed method consists of three key components. First, a perspective projection model acts as a filter, transforming high-resolution images into a lower resolution format, thus lightening the load when identifying the region of interest (ROI). The purpose of this step is to enable laser stripe positioning. Second, we enhance the Gaussian convolutional process by implementing a separable convolutional technique, which decomposes 2-D convolution into two 1-D convolutions, thus lowering computational complexity. Finally, we adopt a dual-layer heterogeneous parallel computing mode, where laser stripe positioning and center extraction tasks are executed in parallel across CPU threads, with each thread utilizing the GPU for computation, enhancing operational efficiency by promoting in-depth collaboration between CPU and GPU. Through extensive experiments, our method demonstrates subpixel-level extraction capabilities in high-resolution laser stripe images, significantly improving execution speed while maintaining extraction accuracy. The findings indicate that the proposed approach has significant real-time application potential in the field of stripe center extraction and lays a solid foundation for improving the measurement precision of structured light.