Research and implementation of parallel Lane detection algorithm based on GPU

Abstract

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.