In the present society, driving safety becomes a very important issue. If there is an excellent driving assistance system, the possibility of a car accident can be significantly reduced. This paper presents a driving assistance system for traffic sign detection and recognition. The proposed technique consists of two subsystem for detection and recognition. First, the road sign detection subsystem adopts the color information to filter out most of irrelevant image regions. The image segmentation and hierarchical grouping are then used to select the candidate road sign region. For the road sign recognition subsystem, Convolution Neural Network (CNN) is adopted to classify the traffic signs for the candidate regions. In the experiments, the proposed technique is carried out using real scene images. The performance evaluation and analysis are provided.
An in-car camera system for traffic sign detection and recognition
2017-06-01
7253210 byte
Conference paper
Electronic Resource
English
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