Abstract:

We present a recognition method based on multiple graphic features to do decision combination on the basis of block kernel function.Firstly,the algorithm extracts two different characteristics of traffic signs, i.e. HOG features and the feature of block kernel function based on submode combination.Secondly,we construct different classifiers for different features accordingly. Finally, the decision fusion is done by the voting mechanism for the outputs of both classifiers.Experiments on Germany Traffic Signs Database prove that our proposal has a higher recognition accuracy compared with the single-feature recognition.

Key words: kernel Fisher nonlinear discriminate analysis;feature combination;block kernel function;traffic sign recognition