Title :
A traffic sign detection pipeline based on interest region extraction
Author :
Salti, Samuele ; Petrelli, Alioscia ; Tombari, Federico ; Fioraio, Nicola ; Di Stefano, Luigi
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Bologna, Bologna, Italy
Abstract :
In this paper we present a pipeline for automatic detection of traffic signs in images. The proposed system can deal with high appearance variations, which typically occur in traffic sign recognition applications, especially with strong illumination changes and dramatic scale changes. Unlike most existing systems, our pipeline is based on interest regions extraction rather than a sliding window detection scheme. The proposed approach has been specialized and tested in three variants, each aimed at detecting one of the three categories of Mandatory, Prohibitory and Danger traffic signs. Our proposal has been evaluated experimentally within the German Traffic Sign Detection Benchmark competition.
Keywords :
feature extraction; image recognition; object detection; traffic engineering computing; German traffic sign detection benchmark competition; danger traffic sign; high appearance variation; illumination; interest region extraction; mandatory traffic sign; prohibitory traffic sign; traffic sign detection pipeline; traffic sign recognition; Benchmark testing; Detectors; Image color analysis; Pipelines; Shape; Training; Transforms;
Conference_Titel :
Neural Networks (IJCNN), The 2013 International Joint Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4673-6128-6
DOI :
10.1109/IJCNN.2013.6706808