Abstract:
In order to overcome the BP neural network, support vector machine (SVM), k nearest neighbor and Bayesian classification's shortcomings which are long training time, complicated programming and operation, bad real-time performance. In this paper, the video vehicle classification algorithm based on C4.5 decision trees is proposed, the design method of the hierarchical classifier is introduced, and the construction process of C4.5 decision trees as an example which was used to divide light-duty vehicle into minibus and van is introduced in detail. Finally, the experimental results demonstrate the effectiveness of the video vehicle classification algorithm based on C4.5 decision trees.