Automatic evaluation of traffic sign visibility using SVM recognition methods
ISCGAV'05 Proceedings of the 5th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
Intelligent System for Traffic Signs Recognition in Moving Vehicles
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Real-Time Road Signs Tracking with the Fuzzy Continuously Adaptive Mean Shift Algorithm
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
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IEEE Transactions on Intelligent Transportation Systems
Pattern Recognition
IEEE Transactions on Intelligent Transportation Systems
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Computer Vision and Image Understanding
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RobVis'08 Proceedings of the 2nd international conference on Robot vision
Distortion invariant road sign detection
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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
Goal evaluation of segmentation algorithms for traffic sign recognition
IEEE Transactions on Intelligent Transportation Systems
Using fourier descriptors and spatial models for traffic sign recognition
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An approach to the recognition of informational traffic signs based on 2-d homography and SVMs
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ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
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Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
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PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Expert Systems with Applications: An International Journal
Triangular traffic signs detection based on RSLD algorithm
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Journal of Real-Time Image Processing
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Information Sciences: an International Journal
Multi-view traffic sign detection, recognition, and 3D localisation
Machine Vision and Applications
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This paper presents an automatic road-sign detection and recognition system based on support vector machines (SVMs). In automatic traffic-sign maintenance and in a visual driver-assistance system, road-sign detection and recognition are two of the most important functions. Our system is able to detect and recognize circular, rectangular, triangular, and octagonal signs and, hence, covers all existing Spanish traffic-sign shapes. Road signs provide drivers important information and help them to drive more safely and more easily by guiding and warning them and thus regulating their actions. The proposed recognition system is based on the generalization properties of SVMs. The system consists of three stages: 1) segmentation according to the color of the pixel; 2) traffic-sign detection by shape classification using linear SVMs; and 3) content recognition based on Gaussian-kernel SVMs. Because of the used segmentation stage by red, blue, yellow, white, or combinations of these colors, all traffic signs can be detected, and some of them can be detected by several colors. Results show a high success rate and a very low amount of false positives in the final recognition stage. From these results, we can conclude that the proposed algorithm is invariant to translation, rotation, scale, and, in many situations, even to partial occlusions