Detection and classification of speed limit traffic signs
This conference paper was presented in the World Congress on Computer Applications and Information Systems, WCCAIS 2014; Hammamet; Tunisia; 17 January 2014 through 19 January 2014 [© 2014 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/WCCAIS.2014.691660...
| Hlavní autoři: | , , |
|---|---|
| Další autoři: | |
| Médium: | Conference paper |
| Jazyk: | English |
| Vydáno: |
© 2014 Institute of Electrical and Electronics Engineers Inc.
2017
|
| Témata: | |
| On-line přístup: | http://hdl.handle.net/10361/7487 http://dx.doi.org/10.1109/WCCAIS.2014.6916605 |
| id |
10361-7487 |
|---|---|
| record_format |
dspace |
| spelling |
10361-74872018-07-25T10:20:20Z Detection and classification of speed limit traffic signs Biswas, Rubel Fleyeh, Hasan Mostakim, Moin Department of Computer Science and Engineering, BRAC University Circular hough transform Classification Digit segmentation SVM Traffic sign This conference paper was presented in the World Congress on Computer Applications and Information Systems, WCCAIS 2014; Hammamet; Tunisia; 17 January 2014 through 19 January 2014 [© 2014 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/WCCAIS.2014.6916605 This paper presents a novel traffic sign recognition system which can aid in the development of Intelligent Speed Adaptation. This system is based on extracting the speed limit sign from the traffic scene by Circular Hough Transform (CHT) with the aid of colour and non-colour information of the traffic sign. The digits of the speed limit sign are then extracted and classified using SVM classifier which is trained for this purpose. In general, the system detects the prohibitory traffic sign in the first place, specifies whether the detected sign is a speed limit sign, and then determines the allowed speed in case the detected sign is a speed limit sign. The SVM classifier was trained with 270 images which were collected in different light conditions. To check the robustness of this system, it was tested against 210 images which contain 213 speed limit traffic sign and 288 Non- Speed limit signs. It was found that the accuracy of recognition was 98% which indicates clearly the high robustness targeted by this system. Published 2017-01-03T10:29:25Z 2017-01-03T10:29:25Z 2014-10 Conference paper Biswas, R., Fleyeh, H., & Mostakim, M. (2014). Detection and classification of speed limit traffic signs. Paper presented at the 2014 World Congress on Computer Applications and Information Systems, WCCAIS 2014, doi:10.1109/WCCAIS.2014.6916605 978-147993351-8 http://hdl.handle.net/10361/7487 http://dx.doi.org/10.1109/WCCAIS.2014.6916605 en http://ieeexplore.ieee.org/document/6916605/ © 2014 Institute of Electrical and Electronics Engineers Inc. |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Circular hough transform Classification Digit segmentation SVM Traffic sign |
| spellingShingle |
Circular hough transform Classification Digit segmentation SVM Traffic sign Biswas, Rubel Fleyeh, Hasan Mostakim, Moin Detection and classification of speed limit traffic signs |
| description |
This conference paper was presented in the World Congress on Computer Applications and Information Systems, WCCAIS 2014; Hammamet; Tunisia; 17 January 2014 through 19 January 2014 [© 2014 IEEE] The conference paper's definite version is available at: http://dx.doi.org/10.1109/WCCAIS.2014.6916605 |
| author2 |
Department of Computer Science and Engineering, BRAC University |
| author_facet |
Department of Computer Science and Engineering, BRAC University Biswas, Rubel Fleyeh, Hasan Mostakim, Moin |
| format |
Conference paper |
| author |
Biswas, Rubel Fleyeh, Hasan Mostakim, Moin |
| author_sort |
Biswas, Rubel |
| title |
Detection and classification of speed limit traffic signs |
| title_short |
Detection and classification of speed limit traffic signs |
| title_full |
Detection and classification of speed limit traffic signs |
| title_fullStr |
Detection and classification of speed limit traffic signs |
| title_full_unstemmed |
Detection and classification of speed limit traffic signs |
| title_sort |
detection and classification of speed limit traffic signs |
| publisher |
© 2014 Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2017 |
| url |
http://hdl.handle.net/10361/7487 http://dx.doi.org/10.1109/WCCAIS.2014.6916605 |
| work_keys_str_mv |
AT biswasrubel detectionandclassificationofspeedlimittrafficsigns AT fleyehhasan detectionandclassificationofspeedlimittrafficsigns AT mostakimmoin detectionandclassificationofspeedlimittrafficsigns |
| _version_ |
1814306971538423808 |