%0 Journal Article %1 noauthororeditor %A Lwin, Myint Tun | Thida %D 2019 %J International Journal of Trend in Scientific Research and Development %K Computing HOG Real-time SVM Threshold Traffic and color computer intelligent recognition sign system transport vision %N 5 %P 2367-2371 %R https://doi.org/10.31142/ijtsrd27929 %T Real Time Myanmar Traffic Sign Recognition System using HOG and SVM %U https://www.ijtsrd.com/computer-science/real-time-computing/27929/real-time-myanmar-traffic-sign-recognition-system-using-hog-and-svm/myint-tun %V 3 %X Traffic sign recognition is one of the most important research topics for enabling autonomous vehicle driving systems. In order to be deployed in driving environments intelligent transport system must be able to recognize and respond to exceptional road conditions such as traffic signs highway work zones and imminent road works automatically. In this paper Real time Myanmar Traffic Sign Recognition System RMTSRS is proposed. The incoming video stream is fed into computer vision. Then each incoming frames are segmented using color threshold method for traffic sign detection. A Histogram of Oriented Gradients HOG technique is used to extract the features from the segmented traffic sign and then RMTSRS classifies traffic sign types using Support Vector Machine SVM . The system achieves classification accuracy up to 98 . Myint Tun | Thida Lwin "Real-Time Myanmar Traffic Sign Recognition System using HOG and SVM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd) ISSN: 2456-6470 Volume-3 | Issue-5 August 2019 URL: https://www.ijtsrd.com/papers/ijtsrd27929.pdfPaper URL: https://www.ijtsrd.com/computer-science/real-time-computing/27929/real-time-myanmar-traffic-sign-recognition-system-using-hog-and-svm/myint-tun

@article{noauthororeditor, abstract = {Traffic sign recognition is one of the most important research topics for enabling autonomous vehicle driving systems. In order to be deployed in driving environments intelligent transport system must be able to recognize and respond to exceptional road conditions such as traffic signs highway work zones and imminent road works automatically. In this paper Real time Myanmar Traffic Sign Recognition System RMTSRS is proposed. The incoming video stream is fed into computer vision. Then each incoming frames are segmented using color threshold method for traffic sign detection. A Histogram of Oriented Gradients HOG technique is used to extract the features from the segmented traffic sign and then RMTSRS classifies traffic sign types using Support Vector Machine SVM . The system achieves classification accuracy up to 98 . Myint Tun | Thida Lwin "Real-Time Myanmar Traffic Sign Recognition System using HOG and SVM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd) ISSN: 2456-6470 Volume-3 | Issue-5 August 2019 URL: https://www.ijtsrd.com/papers/ijtsrd27929.pdfPaper URL: https://www.ijtsrd.com/computer-science/real-time-computing/27929/real-time-myanmar-traffic-sign-recognition-system-using-hog-and-svm/myint-tun }, added-at = {2019-09-12T15:03:35.000+0200}, author = {Lwin, Myint Tun | Thida}, biburl = {https://www.bibsonomy.org/bibtex/2b0eb32bae01f646cca303840c2fdae2c/ijtsrd}, doi = {https://doi.org/10.31142/ijtsrd27929}, interhash = {2ad40634cc358826402bab6484eecf54}, intrahash = {b0eb32bae01f646cca303840c2fdae2c}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Computing HOG Real-time SVM Threshold Traffic and color computer intelligent recognition sign system transport vision}, language = {English}, month = aug, number = 5, pages = {2367-2371}, timestamp = {2019-09-12T15:03:35.000+0200}, title = {Real Time Myanmar Traffic Sign Recognition System using HOG and SVM }, url = {https://www.ijtsrd.com/computer-science/real-time-computing/27929/real-time-myanmar-traffic-sign-recognition-system-using-hog-and-svm/myint-tun}, volume = 3, year = 2019 }