Vehicle Color Recognition Based on CUDA Acceleration

The processing efficiency of Intelligent Transportation System has become an issue which is attracting more and more attention in order to combat vehicle crimes. The vehicle color recognition plays an important role in identifying, searching, improving and enhancing vehicle Intelligent Transportation System. However, area identification or location and surface high light detection are needed before vehicle color recognition. Convolution neural network training algorithm is taken as the best choice to conduct vehicle color recognition for its parameters are less and computation speed is faster. Neural network algorithm is of high parallelism, and its algorithm can even be further optimized if CUDA acceleration is selected. This research results have reference value for improving the processing efficiency of Intelligent Transportation System.