Parallel Accelerated Algorithm Optimization for Speckle Matching in Deformation Measurement Based on Stereo Vision

This paper is concerned with the efficiency of speckle match in vision deformation measurement, upon which the CUDA programming architecture, combined with the Visual Studio platform and Mex script files is utilized to implement parallel operations. With the aid of compiling the GPU parallel mode of the CUDA source program through NVCC, the scheme of speckle matching parallel computing are given, which is crucial to improve the real-time performance of vision-based deformation measurement. Consequently, the method in this paper completes the efficient calculation of match of the speckle image sub-regions in the three-dimensional deformation measurement. The proposed strategy solves the obstacle problem when the Mex script and different programming languages interact, and is not restricted by overloaded functions, so that the overall computing performance of the deformation measurement program reaches a better state. Lastly, the experimental results show that the speckle matching has achieved a calculation speedup ratio of 20.39 times.