TW

Parallel DIC Engine and its application research codes.

Introduction

This repository provides a pipelined real-time DIC system implementation that unifying the computation capabilities of both CPU and GPU. The system framework is based on the figure below:

1. TW_Engine: The revised implementations of the paDIC algorithm to make thame more suitable for real-time systems and applications
2. TW_EngineTester: Use Google Test to perform the unit test of the TW_Engine
3. TW_Core: The implementation of the proposed real-time DIC system.

Dependencies

*Note: Please make sure you have at least one camera connected to the computer before you start.

1. Intel Math Kernel Library (MKL): using fftw3 to do fast Fourier transform (FFT) and LAPACK routine to solve linear system in parlalel on CPU.
2. CUDA 8.0+: for parallel computing on NVIDIA GPUs.
3. CUFFT: associated with CUDA, for perform parallel FFT on GPU.
4. Qt 5.5+ with OpenGL Integration: for GUI and multi-media used in App_DPRA.
5. OpenCV 3.1+: for fast and convenient image I/O.

References

[1] Zhang, L., Wang, T., Jiang, Z., Kemao, Q., Liu, Y., Liu, Z., ... & Dong, S. (2015). High accuracy digital image correlation powered by GPU-based parallel computing. Optics and Lasers in Engineering, 69, 7-12.

[2] Wang, T., Jiang, Z., Kemao, Q., Lin, F., & Soon, S. H. (2016). GPU accelerated digital volume correlation. Experimental Mechanics, 56(2), 297-309.

[3] Wang, T., Kemao, Q., Seah, H. S., & Lin, F. (2018). A flexible heterogeneous real-time digital image correlation system. Optics and Lasers in Engineering, 110, 7-17.