Paper Info
Title
A Method of Detecting and Recognizing Speed-limit Signs
Abstract
This paper proposes a novel speed-limit sign detection and recognition method by using only gray-level information. This method has a real-time processing ability to remind drivers about the speed limit when they are driving on roads, and it contains four main processing modules: speed-limit sign detection, speed-limit sign segmentation, speed-limit sign recognition and system integration. For detecting speed limit signs, both Adaboost and Circular Hough Transform (CHT) are used. For recognizing speed-limit signs, Support Vector Machine is applied and a high recognition performance up to 97.02% is achieved in our experiments. By integrating the four processing modules efficiently, a high efficient speed-limit sign detection and recognition system has been developed.
Year
DOI
Venue
2012
10.1109/IIH-MSP.2012.96
IIH-MSP
Keywords
Field
DocType
speed-limit sign segmentation,speed-limit sign,novel speed-limit sign detection,adaboost,learning (artificial intelligence),cht,traffic engineering computing,recognition system,circular hough transform,image segmentation,speed-limit sign detection,speed limit sign,speed-limit sign recognition,system integration,high recognition performance,recognition method,high efficient speed-limit sign,support vector machine,object detection,object recognition,recognizing speed-limit signs,gray-level information,support vector machine(svm),support vector machines,hough transforms,testing,detectors,learning artificial intelligence
Object detection,Computer vision,AdaBoost,Pattern recognition,Computer science,Segmentation,Support vector machine,Hough transform,Image segmentation,Artificial intelligence,Speed limit,Cognitive neuroscience of visual object recognition
Conference
ISBN
Citations 
PageRank 
978-1-4673-1741-2
1
0.37
References 
Authors
0
3
Name
Order
Citations
PageRank
Yea-shuan Huang147979.42
Yun-Shin Le210.37
Fang-Hsuan Cheng332035.34