Automatic Detection and Recognition of Text-Based Traffic Signs from images

Detection and recognition of texts in traffic signs has been widely studied and with the advance in image capture technology has helped to improve or to create new methods to achieve this issue. In this work, we presented a method for detection, segmentation and recognition of text-based traffic sig...

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Bibliographic Details
Published in:Revista IEEE América Latina 2018-12, Vol.16 (12), p.2947-2953
Main Authors: de Oliveira, Gustavo Henrique, da Silva, Francisco Assis, Pereira, Danillo Roberto, de Almeida, Leandro Luiz, Artero, Almir Olivette, Bonora, Alex Fernando, de Albuquerque, Victor Hugo C.
Format: Article
Language:English
Subjects:
Characters segmentation
Cost analysis
IEEE transactions
Image capture
Image detection
Image recognition
Image segmentation
Matrix decomposition
Object recognition
OCR
Street signs
Text recognition
Traffic control
Traffic signs
Traffic signs detection
Traffic signs recognition
Visualization
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Description
Summary:Detection and recognition of texts in traffic signs has been widely studied and with the advance in image capture technology has helped to improve or to create new methods to achieve this issue. In this work, we presented a method for detection, segmentation and recognition of text-based traffic signs from images analyzing and processing techniques. The results show that the computational cost and accuracy rate considering the proposed approach are acceptable to real time applications, with an execution time under 0.5 seconds, with a hit rate of 94.38% in the plate detection, 83.42% in the character segmentation and 89.23 in the digit classification.
ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2018.8804261