In this paper, a traffic sign recognition algorithm based on logpolar transformation and Zernike moment was presented. First, to improve the image contrast, histogram equalization was performed in HSI color space towards the image captured from complex natural environment. After that, traffic sign was detected by color, and segmentation and region merging was carried out.Next, it’s followed by screening by shape and subsequent normalization. Then, images’ Zernike moment was computed combining logpolar transformation. Lastly, SVM classifier was used to recognize the object. The experiment result shows 94.71% detection accuracy and 85% recognition accuracy, which demonstrates that the traffic sign recognition system can effectively recognize the distortional, scaling or rotated traffic signs.