Paper
19 January 2009 Real-time traffic sign detection and recognition
Author Affiliations +
Proceedings Volume 7257, Visual Communications and Image Processing 2009; 72570A (2009) https://doi.org/10.1117/12.806171
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
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
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ernst Herbschleb and Peter H. N. de With "Real-time traffic sign detection and recognition", Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72570A (19 January 2009); https://doi.org/10.1117/12.806171
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CITATIONS
Cited by 4 scholarly publications and 3 patents.
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KEYWORDS
Image processing

Databases

Image segmentation

Reliability

Detection and tracking algorithms

Panoramic photography

Image filtering

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