Text Detection and Recognition on Traffic Panels From Street-Level Imagery Using Visual Appearance
Traffic sign detection and recognition has been thoroughly studied for a long time. However, traffic panel detection and recognition still remains a challenge in computer vision due to its different types and the huge variability of the information depicted in them. This paper presents a method to detect traffic panels in street-level images and to recognize the information contained on them, as an application to intelligent transportation systems (ITS). The main purpose can be to make an automatic inventory of the traffic panels located in a road to support road maintenance and to assist drivers. This proposal extracts local descriptors at some interest keypoints after applying blue and white color segmentation. Then, images are represented as a “bag of visual words” and classified using Naïve Bayes or support vector machines. This visual appearance categorization method is a new approach for traffic panel detection in the state of the art. Finally, the authors own text detection and recognition method is applied on those images where a traffic panel has been detected, in order to automatically read and save the information depicted in the panels. The authors propose a language model partly based on a dynamic dictionary for a limited geographical area using a reverse geocoding service. Experimental results on real images from Google Street View prove the efficiency of the proposed method and give way to using street-level images for different applications on ITS.
- Record URL:
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
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Supplemental Notes:
- Abstract reprinted with permission of IEEE.
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Authors:
- Gonzalez, Alvaro
- Bergasa, Luis M
- Yebes, J Javier
- Publication Date: 2014-2
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: pp 228-238
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Serial:
- IEEE Transactions on Intelligent Transportation Systems
- Volume: 15
- Issue Number: 1
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1524-9050
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Subject/Index Terms
- TRT Terms: Algorithms; Color; Computer vision; Detection and identification systems; Image processing; Methodology; Traffic signs
- Identifier Terms: Google Street View
- Geographic Terms: Spain
- Subject Areas: Data and Information Technology; Highways; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01527035
- Record Type: Publication
- Files: TLIB, TRIS
- Created Date: May 29 2014 5:19PM