Road-sign detection and tracking
Resource
IEEE Transactions on Vehicular Technology 52 (5): 1329-1341
Journal
IEEE Transactions on Vehicular Technology
Journal Volume
52
Journal Issue
5
Pages
1329-1341
Date Issued
2003
Author(s)
Abstract
In a visual driver-assistance system road-sign detection and tracking is one of the major tasks. This study describes an approach to detecting and tracking road signs appearing in complex traffic scenes. In the detection phase, two neural networks are developed to extract color and shape features of traffic signs from the input scenes images. Traffic signs are then located in the images based on the extracted features. This process is primarily conceptualized in terms of fuzzy-set discipline. In the tracking phase, traffic signs located in the previous phase are tracked through image sequences using a Kalman filter. The experimental results demonstrate that the proposed method performs well in both detecting and tracking road signs present in complex scenes and in various weather and illumination conditions.
Subjects
(HSI) color model; Fuzzy integration; Hue; Intensity; Kalman filter; Neural networks; Road-sign detection and tracking; Saturation
SDGs
Other Subjects
Automobile drivers; Color; Feature extraction; Fuzzy sets; Image analysis; Kalman filtering; Neural networks; Road and street markings; Traffic signs; Road sign detection; Road sign tracking; Visual driver assistance system; Computer vision
Type
journal article
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