Research and implementation of parallel Lane detection algorithm based on GPU

Graphic Processing Unit (GPU) with the powerful computing ability is widely used for Parallel Computing. This paper raised a parallel Lane Detection Algorithm based on GPU acceleration, which could reduce the computing time for processing large amounts of data and solve large-scale complex problems. We implemented Median filter, Differential excitation and Hough transform on compute unified device architecture (CUDA). This algorithm took the advantages of GPU in parallel computation, memory management and reasonably allocated the computational resources and the corresponding computational tasks to the host and device in the Lane Detection. In this paper, different size of the image are processed and the experiment result proved that with the amount of data increases, the GPU acceleration will get good results.

[1]  Dong Hwan Kim,et al.  A Robust Lane Detection Method Based on Vanishing Point Estimation Using the Relevance of Line Segments , 2017, IEEE Transactions on Intelligent Transportation Systems.

[2]  Zhenyu He,et al.  Robust Object Tracking via Key Patch Sparse Representation , 2017, IEEE Transactions on Cybernetics.

[3]  Anil K. Jain.  Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[4]  Monson H. Hayes,et al.  A Novel Lane Detection System With Efficient Ground Truth Generation , 2012, IEEE Transactions on Intelligent Transportation Systems.

[5]  Wang Hong-yuan,et al.  Fast Scale Invariant Feature Transform Algorithm Based on CUDA , 2010 .

[6]  Gang Xu,et al.  Research of Road Extraction Based on Hough Transformation and Morphology , 2012, 2012 International Conference on Computer Science and Service System.

[7]  Pierre Charbonnier,et al.  Robust road marking extraction in urban environments using stereo images , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[8]  Matti Pietikäinen,et al.  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2009, TPAMI-2008-09-0620 1 WLD: A Robust Local Image Descriptor , 2022 .

[9]  Jignesh M. Patel,et al.  Implications of Emerging 3D GPU Architecture on the Scan Primitive , 2015, SGMD.

[10]  Zhiyi Yang,et al.  Parallel Image Processing Based on CUDA , 2008, 2008 International Conference on Computer Science and Software Engineering.

[11]  Youngjoon Han,et al.  A real-time system of lane detection and tracking based on optimized RANSAC B-spline fitting , 2013, RACS.

[12]  Peng Zhao,et al.  A robust lane detection algorithm based on differential excitation , 2016, 2016 International Conference on Machine Learning and Cybernetics (ICMLC).

[13]  H. Pourghassem,et al.  A robust and real-time road line extraction algorithm using hough transform in intelligent transportation system application , 2012, 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE).

[14]  Zhenyu He,et al.  Connected Component Model for Multi-Object Tracking , 2016, IEEE Transactions on Image Processing.

[15]  Youngmin Kim,et al.  Accelerating MATLAB with GPU Computing: A Primer with Examples , 2013 .

[16]  Shutao Li,et al.  Lane detection algorithm based on local feature extraction , 2013, 2013 Chinese Automation Congress.