2006 · 23 citations · 3 references
ComputingAutomotive EngineeringComputer ScienceComputer VisionMachine LearningMachine VisionFeature DetectionImage ClassificationObject DetectionPattern RecognitionShape AnalysisTraffic EngineeringColor SegmentationFeature Extraction For Traffic SignsFrequency Domain ProcessingMulti-layer NetworksSegmentationShapeShape DetectionShape Features
This paper presents a real-time system to detect speed limit signs and remind drivers about the allowable speed limit in a specific road. The developed system consists of two main tasks, namely detection and recognition. In our work, speed limit sign is detected and extracted from real world scenes on the basis of their color and shape features. The detection task is based on a combination of color segmentation and shape detection techniques. It significantly speeds up the shape detection process by calculating the cross-correlation in frequency domain. Next, classification is then performed on extracted candidate region using multi-layer perceptron neural networks. Experiment results proved the feasibility of this system.
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Colour segmentation with polynomial classification
Norbert Bartneck, Walter Ritter · 2003 · 14 citations