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Indonesian traffic sign detection based on Haar-PHOG features and SVM classification

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Adnan, A. W., Yussof, S. and Mahmood, S. 2015. Soft biometrics: gender recognition from unconstrained face images using local feature descriptor. Journal of Information and Communication Technology 14: 111–122, doi: 10.1145/1282280.1282340. Adnan A. W. Yussof S. and Mahmood S. 2015 Soft biometrics: gender recognition from unconstrained face images using local feature descriptor Journal of Information and Communication Technology 14 111 122 , doi: 10.1145/1282280.1282340 Open DOISearch in Google Scholar

Arora, S., Brar, Y. S. and Kumar, S. 2014. Haar wavelet transform for solution of image retrieval. International Journal of Advanced Computer and Mathematical Science 5: 27–31. Arora S. Brar Y. S. and Kumar S. 2014 Haar wavelet transform for solution of image retrieval International Journal of Advanced Computer and Mathematical Science 5 27 31 Search in Google Scholar

Banerji, S., Sinha, A. and Liu, C. 2013a. New image descriptors based on color, texture, shape, and wavelets for object and scene image classification. Neurocomputing 117: 173–185, doi: 10.1016/j.neucom.2013.02.014. Banerji S. Sinha A. and Liu C. 2013a New image descriptors based on color, texture, shape, and wavelets for object and scene image classification Neurocomputing 117 173 185 , doi: 10.1016/j.neucom.2013.02.014 Open DOISearch in Google Scholar

Banerji, S., Sinha, A. and Liu, C. 2013b. HaarHOG: improving the HOG descriptor for image classification. 2013 IEEE International Conference on Systems, Man, and Cybernetics HaarHOG, 4282–4287, doi: 10.1109/SMC.2013.729. Banerji S. Sinha A. and Liu C. 2013b HaarHOG: improving the HOG descriptor for image classification 2013 IEEE International Conference on Systems, Man, and Cybernetics HaarHOG 4282 4287 , doi: 10.1109/SMC.2013.729 Open DOISearch in Google Scholar

Berkaya, S. K., Gunduz, H., Ozsen, O., Akinlar, C. and Gunal, S. 2016. On circular traffic sign detection and recognition. Expert Systems with Applications 48: 67–75, doi: 10.1016/j.eswa.2015.11.018. Berkaya S. K. Gunduz H. Ozsen O. Akinlar C. and Gunal S. 2016 On circular traffic sign detection and recognition Expert Systems with Applications 48 67 75 , doi: 10.1016/j.eswa.2015.11.018 Open DOISearch in Google Scholar

Biswas, R. and Tora, M. R. 2014. LVQ and HOG based speed limit traffic signs detection and categorization. 3rd International Conference on Informatics, Electronics & Vision, 2014, 1–6, doi: 1109/iciev.2014.6850741. Biswas R. and Tora M. R. 2014 LVQ and HOG based speed limit traffic signs detection and categorization 3rd International Conference on Informatics, Electronics & Vision, 2014 1 6 , doi: 1109/iciev.2014.6850741. Search in Google Scholar

Bosch, A. and Zisserman, A. 2007. “Representing shape with a spatial pyramid kernel”, Proceedings of the ACM International Conference on Image and Video Retrieval, Amsterdam, July 9–11, doi: 10.1145/1282280.1282340. Bosch A. and Zisserman A. 2007 . “ Representing shape with a spatial pyramid kernel ”, Proceedings of the ACM International Conference on Image and Video Retrieval Amsterdam, July 9–11, doi: 10.1145/1282280.1282340 Open DOISearch in Google Scholar

Chen, Y., Xie, Y. and Wang, Y. 2013. Detection and recognition of traffic signs based on HSV vision model and shape features. Journal of Computing 8(5): 1366–1370, doi: 10.4304/jcp.8.5.1366-1370. Chen Y. Xie Y. and Wang Y. 2013 Detection and recognition of traffic signs based on HSV vision model and shape features Journal of Computing 8(5 ): 1366 1370 , doi: 10.4304/jcp.8.5.1366-1370 Open DOISearch in Google Scholar

Dai, W., Jiang, J., Ding, G. and Liu, Z. 2019. Development and application of fire video image detection technology in China’s road tunnels. Civil Engineering Journal 5(1): 1–17, doi: 10.28991/cej-2019-03091221. Dai W. Jiang J. Ding G. and Liu Z. 2019 Development and application of fire video image detection technology in China’s road tunnels Civil Engineering Journal 5(1 ): 1 17 , doi: 10.28991/cej-2019-03091221 Open DOISearch in Google Scholar

Dalal, N. and Triggs, B. 2005. Histograms of oriented gradients for human detection. Proceeding 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, Vol. I, 886–893, doi: 10.1109/CVPR.2005.177. Dalal N. and Triggs B. 2005 Histograms of oriented gradients for human detection Proceeding 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, Vol. I 886 893 , doi: 10.1109/CVPR.2005.177 Open DOISearch in Google Scholar

Daubechies, I. 1992. Ten lectures on wavelets. CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 61, Lowell, MA, June 1990, doi: 10.1137/1.9781611970104. Daubechies I. 1992 Ten lectures on wavelets CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 61 Lowell, MA, June 1990 , doi: 10.1137/1.9781611970104 Open DOISearch in Google Scholar

Ellahyani, A., El Ansari, M. and Jaafari, I. El 2016. Traffic sign detection and recognition based on random forests. Applied Soft Computing 46: 805–815, doi: 10.1016/j.asoc.2015.12.041. Ellahyani A. El Ansari M. and Jaafari I. El 2016 Traffic sign detection and recognition based on random forests Applied Soft Computing 46 805 815 , doi: 10.1016/j.asoc.2015.12.041 Open DOISearch in Google Scholar

Escalera, S., Baro, X., Pujol, O., Vitria, J. and Radeva, P. 2011. Traffic-sign Recognition Systems Springer, London, doi: 10.1007/978-1-4471-2245-6_5. Escalera S. Baro X. Pujol O. Vitria J. and Radeva P. 2011 Traffic-sign Recognition Systems Springer London , doi: 10.1007/978-1-4471-2245-6_5 Open DOISearch in Google Scholar

Espejel-García, D., Ortíz-Anchondo, L. R., Alvarez-Herrera, C., Hernandez-López, A., Espejel-García, V. V. and Villalobos-Aragón, A. 2017. An alternative vehicle counting tool using the Kalman filter within MATLAB. Civil Engineering Journal 3(11): 1029–1035, doi: 10.28991/cej-030935. Espejel-García D. Ortíz-Anchondo L. R. Alvarez-Herrera C. Hernandez-López A. Espejel-García V. V. and Villalobos-Aragón A. 2017 An alternative vehicle counting tool using the Kalman filter within MATLAB Civil Engineering Journal 3(11 ): 1029 1035 , doi: 10.28991/cej-030935 Open DOISearch in Google Scholar

Fleyeh, H. 2013. “Traffic sign detection based on AdaBoost color segmentation and SVM classification”, Eurocon, Zagreb, July 1-4, pp. 2005–2010, doi: 10.1109/eurocon.2013.6625255. Fleyeh H. 2013 . “ Traffic sign detection based on AdaBoost color segmentation and SVM classification ”, Eurocon Zagreb, July 1-4 , pp. 2005 2010 , doi: 10.1109/eurocon.2013.6625255 Open DOISearch in Google Scholar

Fleyeh, H. 2015. Traffic sign recognition without color information. Colour and Visual Computing Symposium (CVCS) IEEE, Gjøvik, August 25-26, doi: 10.1109/cvcs.2015.7274886. Fleyeh H. 2015 Traffic sign recognition without color information Colour and Visual Computing Symposium (CVCS) IEEE Gjøvik, August 25-26 , doi: 10.1109/cvcs.2015.7274886 Open DOISearch in Google Scholar

Han, Y., Virupakshappa, K. and Oruklu, E. 2015. Robust traffic sign recognition with feature extraction and k-NN classification methods. IEEE International Conference on Electro/Information Technology (EIT), Dekalb, IL, May 21-23, pp. 484–488, doi: 10.1109/EIT.2015.7293386. Han Y. Virupakshappa K. and Oruklu E. 2015 Robust traffic sign recognition with feature extraction and k-NN classification methods IEEE International Conference on Electro/Information Technology (EIT), Dekalb, IL May 21-23 , pp. 484 488 , doi: 10.1109/EIT.2015.7293386 Open DOISearch in Google Scholar

He, X. and Dai, B. 2016. A new traffic signs classification approach based on local and global features extraction. 2016 6th International Conference on Information Communication and Management A, 121–125, doi: 10.1109/infocoman.2016.7784227. He X. and Dai B. 2016 A new traffic signs classification approach based on local and global features extraction 2016 6th International Conference on Information Communication and Management A 121 125 , doi: 10.1109/infocoman.2016.7784227 Open DOISearch in Google Scholar

Kalistatov, K. D. 2019. Wireless video monitoring of the megacities transport infrastructure. Civil Engineering Journal 5(5): 1033–1040, doi: 10.28991/cej-2019-03091309. Kalistatov K. D. 2019 Wireless video monitoring of the megacities transport infrastructure Civil Engineering Journal 5(5 ): 1033 1040 , doi: 10.28991/cej-2019-03091309 Open DOISearch in Google Scholar

Kassani, P. H., Hyun, J. and Kim, E. 2016. Application of soft histogram of oriented gradient on traffic sign detection. 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAl), 388–392, doi: 10.1109/URAI.2016.7734067. Kassani P. H. Hyun J. and Kim E. 2016 Application of soft histogram of oriented gradient on traffic sign detection 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAl) 388 392 , doi: 10.1109/URAI.2016.7734067 Open DOISearch in Google Scholar

Li, H., Sun, F., Liu, L. and Wang, L. 2015. A novel traffic sign detection method via color segmentation and robust shape matching. Neurocomputing 169: 77–88, doi: 10.1016/j.neucom.2014.12.111. Li H. Sun F. Liu L. and Wang L. 2015 A novel traffic sign detection method via color segmentation and robust shape matching Neurocomputing 169 77 88 , doi: 10.1016/j.neucom.2014.12.111 Open DOISearch in Google Scholar

Maldonado-Bascon, S., Lafuente-Arroyo, S., Gil-Jimenez, P., Gomez-Moreno, H. and Lopez-Ferreras, F. 2007. Road-sign detection and recognition based on support vector machines. IEEE Transactions on Intelligent Transportation Systems 8(2): 264–278, doi: 10.1109/TITS.2007.895311. Maldonado-Bascon S. Lafuente-Arroyo S. Gil-Jimenez P. Gomez-Moreno H. and Lopez-Ferreras F. 2007 Road-sign detection and recognition based on support vector machines IEEE Transactions on Intelligent Transportation Systems 8(2 ): 264 278 , doi: 10.1109/TITS.2007.895311 Open DOISearch in Google Scholar

Mogelmose, A., Trivedi, M. M. and Moeslund, T. B. 2012. Vision-based traffic sign detection and analysis for intelligent driver assistance systems. Perspectives and Survey 13(4): 1484–1497, doi: 10.1109/tits.2012.2209421. Mogelmose A. Trivedi M. M. and Moeslund T. B. 2012 Vision-based traffic sign detection and analysis for intelligent driver assistance systems Perspectives and Survey 13(4 ): 1484 1497 , doi: 10.1109/tits.2012.2209421 Open DOISearch in Google Scholar

Ojala, T., Pietikäinen, M. and Mäenpää, T. 2002. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7): 971–987, doi: 10.1109/TPAMI.2002.1017623. Ojala T. Pietikäinen M. and Mäenpää T. 2002 Multiresolution gray-scale and rotation invariant texture classification with local binary patterns IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7 ): 971 987 , doi: 10.1109/TPAMI.2002.1017623 Open DOISearch in Google Scholar

Razian, S. A. and Mahvash Mohammadi, H. 2017. Optimizing raytracing algorithm using CUDA. Italian Journal of Science & Engineering 1(3): 167–178, doi: 10.28991/ijse-01119. Razian S. A. and Mahvash Mohammadi H. 2017 Optimizing raytracing algorithm using CUDA Italian Journal of Science & Engineering 1(3 ): 167 178 , doi: 10.28991/ijse-01119 Open DOISearch in Google Scholar

Ruta, A., Li, Y. and Liu, X. 2010. Real-time traffic sign recognition from video by class-specific discriminative features. Pattern Recognition 43(1): 416–430, doi: 10.1016/j.patcog.2009.05.018. Ruta A. Li Y. and Liu X. 2010 Real-time traffic sign recognition from video by class-specific discriminative features Pattern Recognition 43(1 ): 416 430 , doi: 10.1016/j.patcog.2009.05.018 Open DOISearch in Google Scholar

Shengchao, F., Le, X. I. N. and Yangzhou, C. 2014. Traffic sign detection based on co-training method. Proceedings of the 33rd Chinese Control Conference, July 28-30, Nanjing, China Traffic, 4893–4898, doi: 10.1109/chicc.2014.6895769. Shengchao F. Le X. I. N. and Yangzhou C. 2014 Traffic sign detection based on co-training method Proceedings of the 33rd Chinese Control Conference July 28-30 Nanjing, China Traffic 4893 4898 , doi: 10.1109/chicc.2014.6895769 Open DOISearch in Google Scholar

Soetedjo, A. and Somawirata, I. K. 2017. Circular traffic sign classification using hogbased ring partitioned matching. International Journal of Smart Sensing and Intelligent Systems 10(3): 735–753, doi: 10.21307/ijssis-2017-232. Soetedjo A. and Somawirata I. K. 2017 Circular traffic sign classification using hogbased ring partitioned matching International Journal of Smart Sensing and Intelligent Systems 10(3 ): 735 753 , doi: 10.21307/ijssis-2017-232 Open DOISearch in Google Scholar

Wahyono, W. and Jo, K. 2014. “A comparative study of classification methods for traffic signs recognition”, 2014 IEEE International Conference on Industrial Technology (ICIT), Vol. 1, pp. 614–619, doi: 10.1109/icit.2014.6895001. Wahyono W. and Jo K. 2014 . “ A comparative study of classification methods for traffic signs recognition ”, 2014 IEEE International Conference on Industrial Technology (ICIT), Vol. 1 , pp. 614 619 doi: 10.1109/icit.2014.6895001 Search in Google Scholar

Wang, Q. 2014. Traffic sign segmentation in natural scenes based on color and shape features. 2014 IEEE Workshop on Advanced Research and Technology in Industry Application Traffic, 374–377, doi: 10.1109/wartia.2014.6976273. Wang Q. 2014 Traffic sign segmentation in natural scenes based on color and shape features 2014 IEEE Workshop on Advanced Research and Technology in Industry Application Traffic 374 377 , doi: 10.1109/wartia.2014.6976273 Open DOISearch in Google Scholar

World Health Organization 2018. Global status report on road safety 2018. World Health Organization, Geneva. World Health Organization 2018 Global status report on road safety 2018 World Health Organization, Geneva Search in Google Scholar

Zaklouta, F. and Stanciulescu, B. 2012. Real-time traffic-sign recognition using tree classifiers. IEEE Transactions on Intelligent Transportation Systems 13(4): 1507–1514, doi: 10.1109/TITS.2012.2225618. Zaklouta F. and Stanciulescu B. 2012 Real-time traffic-sign recognition using tree classifiers IEEE Transactions on Intelligent Transportation Systems 13(4 ): 1507 1514 , doi: 10.1109/TITS.2012.2225618 Open DOISearch in Google Scholar

Zaklouta, F., Stanciulescu, B. and Mask, A. F. 2011. Real-time traffic sign recognition using spatially weighted HOG trees. The 15th International Conference on Advanced Robotics, Tallinn, June 20-23, doi: 10.1109/icar.2011.6088571. Zaklouta F. Stanciulescu B. and Mask A. F. 2011 Real-time traffic sign recognition using spatially weighted HOG trees The 15th International Conference on Advanced Robotics, Tallinn June 20-23 doi: 10.1109/icar.2011.6088571 Search in Google Scholar

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