A Road Detection Algorithm by Boosting Using Feature Combination

Road detection is one of the most important branches of road following. In this paper we propose a classification-based road detection algorithm by boosting. To fully utilize potential region feature correlations and improve the accuracy of classification, this algorithm introduces the feature combination method into road detection. First, an over-completed feature set is constructed on several linear and non-linear combined functions. Second, a correlation feature set is selected from the over-completed feature set by feature selection algorithm. Then, the boosting, the support vector machine and the random forest classifiers are used to evaluate the correlation feature set and the raw feature set. The results of the experiment shows the performance of boosting classifier based on the correlation feature set provides the best outcome.