An Algorithm for Road Sign Detection and Recognition using HOG and SVM
Recognizing traffic signs is a challenging problem; and it has captured the attention of the computer vision community for several decades. Essentially, traffic sign recognition is a multi-class classification problem that has become a real challenge for computer vision and machine learning techniques. We present a system which will detect the road sign with shape detection technique. Further recognition of road sign is carried out using Histogram Oriented Gradient and Support Vector Machine. In this paper all red colour Indian road signs are effectively detected. Although many machine learning approaches are used for traffic sign recognition, they are primarily used for classification, not feature design. Identifying rich features using modern machine learning methods has recently attracted attention and has achieved success in many benchmarks. However these approaches have not been fully implemented in the traffic sign recognition problem. In this paper, we propose a new approach to tackle the traffic sign recognition problem. Recognition part will focus on Circular and Triangular road signs. Results show a high success rate. From these results, we can conclude that the proposed algorithm is invariant to translation, rotation, scale, and, in many situations, even to partial occlusions.
Keywords: Intelligent transport systems, YCbCr colour space, extent, shape detection, projected area, HOG, SVM
Cite this Article:
Nagarkar Priya, Kher Heena R. An Algorithm for Road Sign Detection and Recognition using HOG and SVM. Journal of Operating Systems Development & Trends. 2015; 2(1): 1–6p.
Sanket Rege, Rajendra Memane, Mihir Phatak, et al. 2d Geometric Shape And Color Recognition Using Digital Image Processing. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE). Jun 2013; 2(6).
Gareth Loy, Nick Bames. Fast Shape-based Road Sign Detection for a Driver Assistance System. IEEE Int. C. Int. Robot. 2004; 70–75p.
Erkut Kirmizioglu, Hediye Tuydes-Yaman. Comprehensibility of Traffic Signs among Urban Drivers in Turkey. Accid. Anal. Prev. Elsevier. 2012; 131–141p.
Leonardo Brunoa, Giuseppe Parlaa, Clara Celauro. Improved Traffic Signal Detection and Classification via Image Processing Algorithms. Procedia-Soc. Behav. Sci, Elsevier. 2012; 811–821p.
Elisabet Pérez, Bahram Javidi. Nonlinear Distortion-Tolerant Filters for Detection of Road Signs in Background Noise. IEEE Trans. Veh. Technol. May 2002; 51: 567–576p.
Fatin Zaklouta, Bogdan Stanciulescu. Real-Time Traffic Sign Recognition in Three Stages. Robot. Auton. Syst., Elsevier. 2014; 16–24p.
de la Escalera A, Ma Armingol J, Mata M. Traffic Sign Recognition and Analysis for Intelligent Vehicles. Image Vision Comput., Elsevier. 2003; 247–258p.
Huaping Liu, Yulong Liu, Fuchun Sun. Traffic Sign Recognition using Group Sparse Coding. Information Sciences, Elsevier. 2014; 75–89p.
Hasan Fleyeh. Color Detection and Segmentation for Road and Traffic Signs. IEEE Conf. on Cybernetics and Intelligent Systems(CIS). Dec 2004; 808–813p.
Chiung-Yao Fang, Chiou-Shann Fuh, Sei-Wang Chen. Road-Sign Detection and Tracking. IEEE Trans. Veh. Technol. Sep 2003; 52: 1329–1341p.
Saturnino Maldonado-Bascón, Sergio Lafuente-Arroyo, Pedro Gil-Jiménez, et al. Road-Sign Detection and Recognition Based on Support Vector Machines. IEEE Trans. Intell. Transport. Syst. Jun 2007; 8: 264–278p.
Jack Greenhalgh, Majid Mirmehdi. Real-Time Detection and Recognition of Road Traffic Signs. IEEE Trans. Intell. Transport. Syst. Dec 2012; 13: 1498–1506p.
Paclok P, Novovicova J, Pudil P, et al. Road Sign Classification using Laplace Kernel Classifer. Pattern Recogn. Lett., Elsevier. 2000; 1165–1173p.
Hsu SH, Huang C-L. Road Sign Detection and Recognition using Matching Pursuit Method. Image Vision Comput., Elsevier. 2000; 119–129p.
Miguel Angel Garcia, Miguel Angel Sotelo, Martin Gorostiza E. Traffic Sign Detection in Static Images using Matlab. IEEE Int. C. Int. Robot. 2003; 212–215p.
Reza Oji. An Automatic Algorithm For Object Recognition And Detection Based On Sift Keypoints. Signal & Image Processing: An International Journal (SIPIJ). Oct 2012; 3(5): 29–39p.
Fatin Zaklouta, Bogdan Stanciulescu. Real-Time Traffic-Sign Recognition Using Tree Classifiers. IEEE Trans. Intell. Transport. Syst. Dec 2012; 13: 1507–1514p.
Mario Muñoz-Organero, Víctor Corcoba Magaña. Validating the Impact on Reducing Fuel Consumption by Using an Eco Driving Assistant Based on Traffic Sign Detection and Optimal Deceleration Patterns. IEEE Trans. Intell. Transport. Syst. Jun 2013; 14: 1023–1028p.
Fanga CY, Fuhb CS, Yena PS, et al. An Automatic Road Sign Recognition System Based on a Computational Model of Human Recognition Processing. Comput. Vis. Image Und, Elsevier. 2004; 237–268p.
Bram Alefs, Guy Eschemann, Herbert Ramoser, et al. Road Sign Detection from Edge Orientation Histograms. IEEE Int. Veh. Sym.2007; 993–998p.
- There are currently no refbacks.
This site has been shifted to https://stmcomputers.stmjournals.com/