Automatic surface inspection has been used in the industry to reliably detect all kinds of surface defects and to measure the overall quality of a produced piece. Structured light systems (SLS) are based on the reconstruction of the 3D information of a selected area by projecting several phase-shifted sinusoidal patterns onto a surface. Due to the high speed of production lines, surface inspection systems require extremely fast imaging methods and lots of computational power. The cost of such systems can easily become considerable. The use of standard PCs and Graphics Processing Units (GPUs) for data processing tasks facilitates the construction of cost-effective systems. We present a parallel implementation of the required algorithms written in C with CUDA extensions. In our contribution, we describe the challenges of the design on a GPU, compared with a traditional CPU implementation. We provide a qualitative evaluation of the results and a comparison of the algorithm speed performance on several platforms. The system is able to compute two megapixels height maps with 100 micrometers spatial resolution in less than 200ms on a mid-budget laptop. Our GPU implementation runs about ten times faster than our previous C code implementation.

Date Published: 2 February 2012
PDF: 11 pages
Proc. SPIE 8295, Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II, 829510 (2 February 2012); doi: 10.1117/12.907349

Published in SPIE Proceedings Vol. 8295:
Image Processing: Algorithms and Systems X; and Parallel Processing for Imaging Applications II
Karen O. Egiazarian; John Recker; Guijin Wang; Sos S. Agaian; Atanas P. Gotchev, Editor(s)