Design of an automotive traffic sign recognition system targeting a multi-core SoC implementation
Proceedings of the Conference on Design, Automation and Test in Europe
Real time traffic sign detection using color and shape-based features
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Neural network based smart vision system for driver assistance in extracting traffic signposts
Proceedings of the CUBE International Information Technology Conference
Real-time traffic sign detection with vehicle camera images
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication
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A vision based vehicle guidance system must be able to detect and recognize traffic signs. Traffic sign recognition systems collect information about road signs and helps the driver to make timely decisions, making driving safer and easier. This paper deals with the detection and recognition of traffic signs from image sequences using the colour information. Colour based segmentation techniques are employed for traffic sign detection. In order to improve the performance of segmentation, we used the product of enhanced hue and saturation components. To obtain better shape classification performance, we used linear support vector machine with the Distance to Border features of the segmented blobs. Recognition of traffic signs are implemented using multi-classifier non-linear support vector machine with edge related pixels of interest as the feature.