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Proceedings Paper

Real-time color/shape-based traffic signs acquisition and recognition system
Author(s): Sergio Saponara
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Paper Abstract

A real-time system is proposed to acquire from an automotive fish-eye CMOS camera the traffic signs, and provide their automatic recognition on the vehicle network. Differently from the state-of-the-art, in this work color-detection is addressed exploiting the HSI color space which is robust to lighting changes. Hence the first stage of the processing system implements fish-eye correction and RGB to HSI transformation. After color-based detection a noise deletion step is implemented and then, for the classification, a template-based correlation method is adopted to identify potential traffic signs, of different shapes, from acquired images. Starting from a segmented-image a matching with templates of the searched signs is carried out using a distance transform. These templates are organized hierarchically to reduce the number of operations and hence easing real-time processing for several types of traffic signs. Finally, for the recognition of the specific traffic sign, a technique based on extraction of signs characteristics and thresholding is adopted. Implemented on DSP platform the system recognizes traffic signs in less than 150 ms at a distance of about 15 meters from 640x480-pixel acquired images. Tests carried out with hundreds of images show a detection and recognition rate of about 93%.

Paper Details

Date Published: 19 February 2013
PDF: 6 pages
Proc. SPIE 8656, Real-Time Image and Video Processing 2013, 86560C (19 February 2013); doi: 10.1117/12.2001866
Show Author Affiliations
Sergio Saponara, Univ. degli Studi di Pisa (Italy)

Published in SPIE Proceedings Vol. 8656:
Real-Time Image and Video Processing 2013
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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