The Automatic Detection and Recognition of the Traffic Sign

摘要

In this paper, we propose a novel automatic traffic sign detection and recognition method. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost. Segmentation is implemented by the improved Grab cut via the detection information. Classification is defined as a multiclass categorization problem, which is solved by HOG feature and support vector machine. The segmentation task is fulfilled in a fully automatic manner. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination.