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Examples for such regulations are \u2018traffic light ahead\u2019 or \u2018pedestrian crossing\u2019 indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.<\/jats:p>","DOI":"10.3390\/s17040853","type":"journal-article","created":{"date-parts":[[2017,4,13]],"date-time":"2017-04-13T10:55:44Z","timestamp":1492080944000},"page":"853","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2172-7041","authenticated-orcid":false,"given":"Kh","family":"Islam","sequence":"first","affiliation":[{"name":"Department of Artificial Intelligence, Faculty of Computer Science &amp; Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8627-1113","authenticated-orcid":false,"given":"Ram","family":"Raj","sequence":"additional","affiliation":[{"name":"Department of Artificial Intelligence, Faculty of Computer Science &amp; Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,4,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Malik, R., Khurshid, J., and Ahmad, S.N. 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