ORIENTAL JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY www.computerscijournal.org ISSN: 0974-6471 August 2015, Vol. 8, No. (2): Pgs. 137-141 An International Open Free Access, Peer Reviewed Research Journal Published By: Oriental Scientific Publishing Co., India. Traffic Sign Symbol Recognition Using Single Dimension PCA SHASHIDHAR T HALAKATTI 1 and SHAMBULINGA T HALAKATTI 2 1 Department of Computer Science and Engineering ,Rural Engineering College, Hulkoti, India. 2 Department of Electronics & Communication Engineering ,BVVS Polytechnic, Bagalkot, India. (Received: April 25, 2015; Accepted: June 11, 2015) ABSTRACT In this paper, the image processing method has been used to recognize traffic sign symbol from the static image. In this paper we have to recognize traffic sign symbol by using single dimension principal component analysis(sdpca).We have focused on traffic sign symbol of triangular shapes .Images are preprocessed with several image preprocessing techniques, such as threshold techniques, Gaussian filter and Canny edge detection then the single dimension principal component analysis algorithm stages are performed to recognize the traffic sign symbol. Key words: Classification, Feature Extraction, Single Dimension PCA. If the vehicle have these technologies, then we save the life of driver as well as we can have great potential to save precious life of a driver. Now a days every vehicle are embedded with these kind of technologies for the safer drive. For the driver to assist in the high ways. The traffic sign symbols are installed at the side of the road for precaution for the driver to safely drive and reach the destination properly. This paper helps us to detections of traffic sign symbol in order to warn drivers to perform certain actions. Generally, traffic sign symbol provide the driver with a variety of information for safe and efficient navigation. This paper is proposed to develop an efficient algorithm for recognize the traffic sign symbol in a static image. The objective of this algorithm is to reduce the search space in the static image and indicate only region of interest for the efficiency and accurate recognize the traffic sign symbol. In the recent technologies, the identification and recognition of traffic signs have been developed in many research centers. A vision system for the traffic sign recognition and integrated autonomous vehicle was developed as part of the European research project PROMETHEUS at DAIMLER- BENZ Research center [1]. Moreover, many new technologies have been developed for traffic sign recognition. Recognition of traffic sign based on their color and shape features extracted using human vision model by X.W.Gao, L. Podladchokova, D.Shaposhnikov, K.Hong, N.Shevtso [3].However this took a more amount of time and resources. A genetic algorithm was also proposed by Aoyagi