International Journal of Computer Applications (0975 – 8887) Volume 120 – No.24, June 2015 10 Traffic Road Sign Detection and Recognition for Automotive Vehicles Md. Safaet Hossain Department of Electrical Engineering and Computer Science North South University, Dhaka Bangladesh Zakir Hyder Department of Electrical Engineering and Computer Science North South University, Dhaka Bangladesh ABSTRACT Traffic road sign detection and recognition is important to transport system with a robotic eyes or camera while driving in the road. This paper presents and overview the traffic road sign detection and recognition, we developed and implemented the procedure to extract the road sign from a natural complex image. The main objective of this paper is to design and construct a computer based system which can automatically detect the direction of the road sign. This paper is based upon a major approach to detect the direction. In this paper, we will demonstrate the basic idea of how detect the area and extract it. This system will play an important role for the detection purpose of specific domains like island, schools, traffic sign, universities, hospitals, offices etc. Keywords Web based applicatoin testing, performance testing, functional testing, test methods integration, e-commece. 1. INTRODUCTION The sign which is placed at the side of roads to impart information to road users is known as road signs or traffic signs. There are four types of traffic signs that are shown in the traffic code: a) warning; b) prohibition; c) obligation; and d) informative. Depending on the form and the color, the warning signs are equilateral triangles with one vertex upwards. They have a white background and are surrounded by a red border. Prohibition signs are circles with a white or blue background and a red border. Both warning signs and prohibition signs have a yellow background if they are located in an area where there are public works. To indicate obligation, the signs are circles with a blue background. Informative signs have the same color. Finally, there are two exceptions: a) the yield sign, an inverted triangle; and the stop sign, a hexagon. To detect the position of the sign in the image, we must know the two properties i.e., color and shape. The applications and the difficulty of road sign detection make road sign detection an interesting problem. In terms of applications, road sign detection is quite important for the road sign recognition problem, since it is the most important step for a road sign recognition system. So far, the researchers have mainly focused on the road sign recognition problem, in which the task of finding road sign in an arbitrary background is usually avoided by either manual segmentation of the input image, or by capturing faces against a known uniform background. In the last decade, road sign detection has attracted great attention, as road sign recognition system requires automatic road sign detection as a first step, especially for images with cluttered background. Road sign detection also has potential applications in human computer interface and surveillance systems. Road sign detection is difficult due to three main reasons. First, there is a large component of non-rigidity and textural differences among road sign. Second, road sign detection is also made difficult because of additional features, such as dust, which can either be present or totally absent from a road sign. All these additional features increase the variability of the road sign patterns that a road sign detection system should handle. Third, the presence of unpredictable imaging conditions in an unconstrained environment increases the difficulty of the task. A change in light source distribution can cause a significant change in the appearance of the road sign image. All these things should be taken into consideration when designing a road sign detection system. 2. METHODOLOGY Real time road sign detection system has been developed by sequence of operations. To achieve a successful road sign detection system we use following methodologies:  Studying literature on different road sign detection methods and image processing.  Studying the existing method for road sign detection.  Analyze and design for the proposed system.  Implement the proposed design of the road sign detection.  Carrying out experiment and evaluate the system. The performance of the system has been tested and achieved its desired goal. It was captured by a digital camera and able to detect road sign properly with in a natural image. 3. RELATED WORK There are many researches in the literature deal with Road Sign Recognition (RSR) problem. In this section, we will explore some of those approaches. 3.1 Fast grey scale road sign model matching and recognition Mobile Mapping is a standard technique for compiling cartographic information from a mobile vehicle. [1] author paper proposes a novel method for modeling the recognition in a Mobile Mapping process that consists in fitting a model to recover the sign distortion and applying recognition techniques on weak classifiers cascade results. High variance of sign appearance has made the detection and recognition of road signs a computer vision problem over which many studies have lately been performed. There are two main approaches in this field, the color-based and the grayscale- based sign recognition. Color-based approach allows reducing