Since last two decades researches have been working on developing systems that can assists drivers in the best way possible and make driving safe. Computer vision has played a crucial part in design of these systems. With the introduction of vision techniques various autonomous and robust real-time traffic automation systems have been designed such as Traffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among these automatic detection and recognition of road signs has became an interesting research topic. The system can assist drivers about signs they don’t recognize before passing them. Aim of this research project is to present an Intelligent Road Sign Recognition System based on state-of-the-art technique, the Support Vector Machine. The project is an extension to the work done at ITS research Platform at Dalarna University [25]. Focus of this research work is on the recognition of road signs under analysis. When classifying an image its location, size and orientation in the image plane are its irrelevant features and one way to get rid of this ambiguity is to extract those features which are invariant under the above mentioned transformation. These invariant features are then used in Support Vector Machine for classification. Support Vector Machine is a supervised learning machine that solves problem in higher dimension with the help of Kernel functions and is best know for classification problems.