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• W3102247145 abstract "Road sign recognition is one of the core technologies in Intelligent Transport Systems. In the current study, a robust and real-time method is presented to identify and detect the roads speed signs in road image in different situations. In our proposed method, first, the connected components are created in the main image using the edge detection and mathematical morphology and the location of the road signs extracted by the geometric and color data; then the letters are segmented and recognized by Multiclass Support Vector Machine (SVMs) classifiers. Regarding that the geometric and color features ate properly used in detection the location of the road signs, so it is not sensitive to the distance and noise and has higher speed and efficiency. In the result part, the proposed approach is applied on Iranian road speed sign database and the detection and recognition accuracy rate achieved 98.66% and 100% respectively." @default.
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• W3102247145 date "2014-01-05" @default.
• W3102247145 modified "2023-09-27" @default.
• W3102247145 title "Optimized Method for Iranian Road Signs Detection and Recognition System" @default.
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• W3102247145 doi "https://doi.org/10.7815/ijorcs.41.2014.077" @default.
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