@inproceedings{168eec603b804c9eb8347e4f5ea20891,
title = "Real-Time Traffic Sign Detection and Recognition",
abstract = "The continuous growth of imaging databases increasingly requires analysis tools for extraction of features. In this paper, a new architecture for the detection of traffic signs is proposed. The architecture is designed to process a large database with tens of millions of images with a resolution up to 4,800x2,400 pixels. Because of the size of the database, a high reliability as well as a high throughput is required. The novel architecture consists of a three-stage algorithm with multiple steps per stage, combining both color and specific spatial information. The first stage contains an area-limitation step which is performance critical in both the detection rate as the overall processing time. The second stage locates suggestions for traffic signs using recently published feature processing. The third stage contains a validation step to enhance reliability of the algorithm. During this stage, the traffic signs are recognized. Experiments show a convincing detection rate of 99%. With respect to computational speed, the throughput for line-of-sight images of 800×600 pixels is 35 Hz and for panorama images it is 4 Hz. Our novel architecture outperforms existing algorithms, with respect to both detection rate and throughput",
author = "E. Herbschleb and {With, de}, P.H.N.",
year = "2010",
doi = "10.1117/12.806171",
language = "English",
isbn = "978-0-8194-7507-7",
series = "Proceedings of SPIE",
publisher = "SPIE",
pages = "7257--OA1/2",
booktitle = "Proceedings of Visual Communications and Image Processing VCIP 2009, 18-22 January, 2009, San Jose, California",
address = "United States",
note = "Visual Communications and Image Processing 2009 (VCIP 2009), January 20–22, 2009, San Jose, CA, USA, VCIP 2009 ; Conference date: 20-01-2009 Through 22-01-2009",
}