참고문헌
- Han, Y.: Real-time traffic sign recognition based on Zynq FPGA and ARM SoCs, Proc. 2014 IEEE Intl. Conf. Electro/Information Technology (EIT), pp. 373-376, 2014.
- Hoang, A.T., Yamamoto, M., Koide, T.: Low cost hardware implementation for traffic sign detection system, Proc. 2014 IEEE Asia Pacific Conf. Circuits and Systems (APCCAS2014), pp. 363-366, 2014.
- Irmak, M.: Real time traffic sign recognition system on FPGA, Master Thesis, The Graduate School of Natural and Applied Sciences of Middle East Technical University, 2010.
- Ishizuka, Y., and Hirai, Y.: Recognition system of road traffic signs using opponent-color filter, Technical report of IEICE, No. 103, pp. 13-18, 2004, (in Japanese).
- Keller, C. G., et al.: Real-time recognition of U.S. speed signs, Proc. Intl. IEEE Intelligent Vehicles Symposium, pp. 518-523, 2008.
- Liu, W., et al.: Real-time speed limit sign detection and recognition from image sequences, Proc. 2014 IEEE Intl. Conf. Artificial Intelligence and Computational Intelligence (AICI), pp. 262-267, 2010.
- Miura, J., et al.: An active vision system for realtime traffic sign recognition, Proc. Intl. IEEE Conf. Intelligent Transportation Systems, pp. 52-57, 2000.
- Moutarde, F., et al.: Robust on-vehicle real-time visual detection of American and European speed limit signs, with a modular traffic signs recognition system, Proc. Intl. IEEE Intelligent Vehicles Symposium, pp. 1122-1126, 2007.
- Muller, M., et al.: Design of an automotive traffic sign recognition system targeting a multi-core SoC implementation, Proc. Design, Automation & Test in Europe Conference & Exhibition 2010, pp. 532-537, 2010.
- Ozcelik, P. M., et al.: A template-based approach for real-time speed limit sign recognition on an embedded system using GPU computing, Proc. 32nd DAGM Conf. Pattern Recognition, pp. 162-171, 2010.
- Raiyn, J.,and Toledo, T.: Real-time road traffic anomaly detection, Journal of Transportation Technologies, 2014, No. 4, pp. 256-266, 2014.
- Schewior, G., et al.: A hardware accelerated configurable ASIP architecture for embedded realtime video-based driver assistance applications, Proc. 2011 IEEE Intl. Conf. Embedded Computer Systems (SAMOS), pp. 18-21, 2011.
- Soendoro, D., and Supriana, I.: Traffic sign recognition with color based method, shape-arc estimation and SVM, Proc. 2014 IEEE Intl. Conf. Electrical Engi-neering and Informatics (ICEEI), pp. 1-6, 2011.
- Souani, C., Faiedh, H., and Besbes, K.: Efficient algorithm for automatic road sign recognition and its hardware implementation, Journal of Real-Time Image Processing, Vol. 9, Issue 1, pp. 79-93, 2014. https://doi.org/10.1007/s11554-013-0348-z
- Takagi, M., and Fujiyoshi, H.: Road sign recognition using SIFT feature, Proc. 18th Symposium on Sensing via Image Information, LD2-06, 2007, (in Japanese).
- Torresen, J., et al.: Efficient recognition of speed limit signs, Proc. 7th Intl. IEEE Conf. Intelligent Transportation Systems, pp. 652-656, 2004.
- Waite, S. and Oruklu, E.: FPGA-based traffic sign recognition for Advanced Driver Assistance Systems, Journal of Transportation Technologies, Vol. 3, No. 1, pp. 1-16, 2013.
- Yamamoto, M., Hoang, A-T., Koide, T.: Speed traffic sign recognition algorithm for real-time driving assistant system, Proc. 18th Workshop on Synthesis And System Integration of Mixed Information Technologies (SASIMI 2013), pp. 195-200, 2013.
- Zaklouta, F. and Stanciulescu, B.: Segmentation masks for real-time traffic sign recognition using weighted HOG-based trees, Proc. 14th Intl. IEEE Conf. Intelligent Transportation Systems (ITSC), pp. 1954-1959, 2011.
- Zaklouta, F., Stanciulescu, B.: Real-time traffic sign recognition in three stages, Journal of Robotics and Autonomous Systems, Vol 62, Issue 1, pp. 16-24, 2014. https://doi.org/10.1016/j.robot.2012.07.019
- Ciresan, D., et al.: Multi-column deep neural network for traffic sign classification, Journal of Neural Networks, Vol 32, pp. 333-338, 2012. https://doi.org/10.1016/j.neunet.2012.02.023
- Sermanet, P., LeCun, Y.: Traffic sign recognition with multi-scale convolutional networks, Proc. Intl. Joint IEEE Conf. on Neural Networks (IJCNN), pp. 2809-2813, 2011.
- Zaklouta, F., Stanciulescu, B., and Hamdoun. O: Traffic sign classification using K-d trees and random forests, Proc. Intl. Joint IEEE Conf. on Neural Networks (IJCNN), pp. 2151-2155, 2011.
- Article (CrossRef Link), access at March, 15th, 2015
- Article (CrossRef Link), access at June, 10th, 2015.
- Hoang, A-T., Yamamoto, M., Koide, T.: Simple yet effective two-stage speed traffic sign recognition for robust vehicle environments, Proc. 30th Intl. Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2015), pp.420-423, 2015.