Abstract: This paper proposed a support vector machine (SVM)-based road speed limit signs recognition method. In order to improve the recognition performance of the algorithm, an adaptive learning particle swarm optimisation (ALP- SO) algorithm was employed to optimize the parameters of SV呱The proposed ALPSO may adjust its learning parame- ters during the evolutionary process to coordinate the local search with the global search of the PSO algorithm. Experi- mental results show that the proposed ALPSC}SVM is superior to the traditional SVM in terms of the recognition rate, and it's convergence performance is better than the standard PSC}SVM.

Key words: Speed limit signs recognition, Particle swarm optimization, Support vector machine, Parameters optimization