Pattern Recognition Based Detection Recognition of Traffic Sign Using SVM

The objective of this work describes a method for Traffic sign detection and recognition from the traffic panel board(signage). It detect the traffic signs especially for Indian conditions. Images are acquired through the camera and it is invariant to size then it is scaled. It consist of the following steps, first, it detect the traffic sign, if it has sufficient contrast from the background then we use sobel edge detection technique and morphological dilation. Second, extract the detected traffic sign from the board using row count and column count. Third, to extract the feature using DCT, DWT and Hybrid DWTDCT. In training phase, DCT 20 highest energy coefficients are extracted, In DWT 300 features extracted from each traffic sign and in Hybrid DWT-DCT 20 features are extracted. Finally recognition are performed through SVM. The application is to improve the efficiency of transportation networks through applications of communication visually impaired person wear the camera to identify the traffic destination board. Experimental results show that state-of-the-art algorithms obtains highly competitive performance and is especially efficient to different levels of corruptions. The performance of Traffic Sign recognition is evaluated for Traffic Sign board image and the system achieves a recognition rate of 86% using DCT, 90% using DWT and 96% using Hybrid DWT-DCT and SVM. spal_yughu@yahoo.com Keyword-Row count, Column count, DCT, DWT, Hybrid DWT-DCT, SVM.