Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System
This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the i...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2012-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/12/2/1148/ |
| _version_ | 1811306914793914368 |
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| author | Miguel Gavilán Estefanía Arroyo Jorge Pozuelo David F. Llorca Manuel Ocaña Miguel A. García-Garrido |
| author_facet | Miguel Gavilán Estefanía Arroyo Jorge Pozuelo David F. Llorca Manuel Ocaña Miguel A. García-Garrido |
| author_sort | Miguel Gavilán |
| collection | DOAJ |
| description | This paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance. |
| first_indexed | 2024-04-13T08:54:10Z |
| format | Article |
| id | doaj.art-27140d6e1bc64a0dbaf88d4a73c2b560 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T08:54:10Z |
| publishDate | 2012-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-27140d6e1bc64a0dbaf88d4a73c2b5602022-12-22T02:53:22ZengMDPI AGSensors1424-82202012-01-011221148116910.3390/s120201148Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication SystemMiguel GavilánEstefanía ArroyoJorge PozueloDavid F. LlorcaManuel OcañaMiguel A. García-GarridoThis paper presents a complete traffic sign recognition system based on vision sensor onboard a moving vehicle which detects and recognizes up to one hundred of the most important road signs, including circular and triangular signs. A restricted Hough transform is used as detection method from the information extracted in contour images, while the proposed recognition system is based on Support Vector Machines (SVM). A novel solution to the problem of discarding detected signs that do not pertain to the host road is proposed. For that purpose infrastructure-to-vehicle (I2V) communication and a stereo vision sensor are used. Furthermore, the outputs provided by the vision sensor and the data supplied by the CAN Bus and a GPS sensor are combined to obtain the global position of the detected traffic signs, which is used to identify a traffic sign in the I2V communication. This paper presents plenty of tests in real driving conditions, both day and night, in which an average detection rate over 95% and an average recognition rate around 93% were obtained with an average runtime of 35 ms that allows real-time performance.http://www.mdpi.com/1424-8220/12/2/1148/traffic sign recognitionadvanced driver assistance systemsI2Vcomputer vision |
| spellingShingle | Miguel Gavilán Estefanía Arroyo Jorge Pozuelo David F. Llorca Manuel Ocaña Miguel A. García-Garrido Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System Sensors traffic sign recognition advanced driver assistance systems I2V computer vision |
| title | Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System |
| title_full | Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System |
| title_fullStr | Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System |
| title_full_unstemmed | Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System |
| title_short | Complete Vision-Based Traffic Sign Recognition Supported by an I2V Communication System |
| title_sort | complete vision based traffic sign recognition supported by an i2v communication system |
| topic | traffic sign recognition advanced driver assistance systems I2V computer vision |
| url | http://www.mdpi.com/1424-8220/12/2/1148/ |
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