Title :
Real-time traffic sign detection and recognition for in-car driver assistance systems
Author :
Oruklu, Erdal ; Pesty, Damien ; Neveux, Joana ; Guebey, Jean-Emmanuel
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
Abstract :
This paper presents a new computer vision design flow for real time detection and recognition of traffic signs. Autonomous traffic sign detection can play a crucial role in many applications related to transportation safety and geographical information systems. The challenges that need to be addressed include the necessity for robust and accurate detection as well as the high computational requirements of the algorithms. Therefore, we develop a three stage algorithm that is based on i) detection of traffic sign locations using HSV color space, ii) detection of traffic signs using discriminative features and iii) recognition of traffic signs using interest point descriptors. The results show a robust detection and recognition performance for multiple signs and the algorithm can be executed in real-time.
Keywords :
computer vision; driver information systems; feature extraction; image colour analysis; object detection; object recognition; road safety; HSV color space; autonomous traffic sign detection; computer vision design flow; discriminative features; geographical information system; in-car driver assistance systems; interest point descriptors; real-time traffic sign detection; three stage algorithm; traffic sign location detection; traffic sign recognition; transportation safety; Algorithm design and analysis; Databases; Feature extraction; Image color analysis; Labeling; Real time systems; Shape;
Conference_Titel :
Circuits and Systems (MWSCAS), 2012 IEEE 55th International Midwest Symposium on
Conference_Location :
Boise, ID
Print_ISBN :
978-1-4673-2526-4
Electronic_ISBN :
1548-3746
DOI :
10.1109/MWSCAS.2012.6292185