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Streetlight Objects Recognition by Region and Histogram Features in an Autonomous Vehicle System
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In this paper Streetlight object identification is addressed using the notion of image processing. An approach based on Image Processing Techniques is proposed for selection and processing of features from the images. Histogram and Region was applied on the extracted images. Histogram and Region features were then extracted and employed to train the Support Vector Machine (SVM) classifier for streetlight recognition. Experimental results shows 99.1%, 84% and 100% for histogram, region features and combination of both respectively. Experimental results have proved that the proposed method is robust, accurate, and powerful in object recognition.
Keywords
Streetlight Recognition, Autonomous Vehicles, Image Histogram Features, Region Features, Support Vector Machine.
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- S. Bagloee, M. Tavana, M. Asadi and T. Oliver, “Autonomous Vehicles: Challenges, Opportunities, and Future Implications for Transportation Policies”, Journal of Modern Transportation, Vol. 24, No. 4, pp. 284-303, 2016.
- K. Waterloo, “Fairway Road Lanes Closed After Car Collides with Streetlight”, Available at: https://www.cbc.ca/news/canada/kitchener-waterloo/fairway-road-south-car-accident-1.4432176, Accessed on 2017.
- A. Rao, A. Angadi, B. Bhagyashree and R. Chaitra, “Vision-Based Road Hump and Speed Breaker Detection”, Available at: http://www.kscst.iisc.ernet.in/spp/40_series/SPP40S/02_Exhibition_Projects/183_40S_BE_1421.pdf
- H. Ward, “Night-Time Accidents, a Scoping Study”, Available at: https://rospa.com/report/ nighttimeaccidents, Accessed on 2017.
- C. Atagi, “Busy Palm Springs Intersection Shutdown after Two Cars Collide, Knock Over Street Light”, Available at: https://www.desertsun.com/story/news/traffic/2017/10/16/busy-palm-springs-intersection-shutdown-after-two-cars-collide-knock-over-street-light/768710001/, Accessed on 2017.
- C. Pocock, “Body, Face and Rectangle Detection: A Literature Review”, Available at: https://people.cs.uct.ac.za/~jnorman/virpan/downloads/literature_review/literature_review-chris.pdf, Accessed on 2012.
- Y. Ramadevi, T. Sridevi, B. Poornima, and B. Kalyani, “Segmentation and Object Recognition using Edge Detection Techniques”, International Journal of Computer Science and Information Technology, Vol. 2, No. 6, pp. 1-12, 2010.
- M.E. Irhebhude, “Object Detection, Recognition and Re-Identification in Video Footage”, PhD Dissertation, Department of Information and Computing Science, Loughborough University, 2015.
- Mathworks, “Object Detection in Computer Vision”, Available at: https://www.mathworks.com/discovery/object-detection.html, Accessed on 2018.
- N. Dalal and B. Triggs, “Histograms of Oriented Gradients for Human Detection”, Proceedings of International Conference on Computer Vision and Pattern Recognition, pp. 886-893, 2005.
- S. Bindu, S. Prudhvi, G. Hemalatha, R. Sekhar and V. Nanchariah, “Object Detection from Complex Background Image using Circular Hough Transform”, Journal of Engineering Research and Applications, Vol. 4, No. 4, pp. 23-28, 2014.
- M. Yadollahi and A. Prochazka, “Image Segmentation for Object Detection”, Available at: http://dsp.vscht.cz/konference_matlab/MATLAB11/prispevky/129_yadollahi.pdf
- S. Vijayalakshmi and C. Durairaj, “Use of Multiple Thresholding Techniques for Moving Object Detection and Tracking”, International Journal of Computer Applications, Vol. 80, No. 1, pp. 12-18, 2013.
- A. Shubham and J. Singh, “Object Detection by Colour Threshold Method”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 4, No. 10, pp. 1-9, 2015.
- K. Anusha and K. Sirisha, “Breaking the Speed Breakers using Image Processing”, Available at: https://www.scribd.com/document/54957257/Breaking-the-Speed-Breakers-Using-Image-Processing-1-2, Accessed on 2011.
- R. Hussin, M. Juhari, N. Kang, R. Ismail and A. Kamarudin, “Digital Image Processing Techniques for Object Detection from Complex Background Image”, Proceedings of International Conference on Robotics and Intelligent Sensors, pp. 167-174, 2012.
- A. Danti, J. Kulkarni, S. Jyothi and P.S. Hiremath, “A Technique for Bump Detection in Indian Road Images Using Color Segmentation and Knowledge Base Object Detection”, International Journal of Scientific and Engineering Research, Vol. 4, No. 8, pp. 1-5, 2013.
- P. Kanubha and Y. Parmar, “A Research-Develop An Efficient Algorithm To Recognize, Separate and Count Indian Coin From Image Using Matlab”, International Journal of Modern Trends in Engineering and Research, Vol. 3, No. 2, pp. 26-34, 2012.
- M.E. Irhebhude, M. Ali and E. Edirisinghe, “Pedestrian Detection and Vehicle Type Recognition”, Proceedings of International Conference on Intelligent Computer Communication and Processing, pp. 1-5, 2015.
- R. Mallikka and M. Balamurugan, “Shape Based Feature Extraction in Detection of Image”, Proceedings of International Conference on Computational Intelligence, pp. 1-6, 2018.
- R. Kate and S. Chitode, “Number Plate Recognition using Segmentation”, International Journal of Engineering Research and Technology, Vol. 1, No. 9, pp. 41-47, 2012.
- M. Kiadtikornthaweeyot and A. Tatnall, “Region of Interest Detection based on Histogram Segmentation For Satellite Image”, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 11, No. 7, pp. 249-255, 2016
- N. Otsu, “A Threshold Selection Method from Gray-Level Histograms”, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 9, No. 1, pp. 62-66, 1979.
- N. Senthilkumaran and S. Vaithegi, “Image Segmentation by using Thresholding Techniques for Medical Images”, Computer Science and Engineering: An International Journal, Vol. 6, No. 1, pp. 41-47, 2016.
- P. Kanungo, P. Kumar and S. Umesh, “Image Segmentation using Thresholding and Genetic Algorithm”, Journal of Electrical and Computer Engineering, Vol. 2017, pp. 1-10, 2017.
- L. Christodoulou, K. Takis and O. Marques, “Advanced Statistical and Adaptive Threshold Techniques for Moving Object Detection and Segmentation”, Proceedings of 3rd International Conference on Digital Signal Processing, pp. 1-8, 2011.
- Segmentation, Available at: http://www.bioss.ac.uk/people/chris/ch4.pdf.
- A. Coste, “Histograms”, Available at: http://www.sci.utah.edu/~acoste/uou/Image/project1/Arthur_COSTE_Project_1_report.html.
- S. Patel and P. Tandel, “A Survey on Feature Extraction Techniques for Shape based Object Recognition”, International Journal of Computer Applications, Vol. 137, No. 6, pp. 16-20, 2016.
- D. Zhang and L. Guojun, “Review of Shape Representation and Description Techniques”, Pattern Recognition, Vol. 37, No. 1, pp. 1-19, 2004.
- M.E. Irhebhude, A. Nawahda and E. Edirisinghe, “View Invariant Vehicle Type Recognition and Counting System using Multiple Features”, International Journal of Computer Vision and Signal Processing, Vol. 6, No. 1, pp. 20-32, 2016.
- S. Milan, H. Vaclav and B. Roger, “Image Processing Analysis, and Machine Vision”, 3rd Edition, CL Engineering, 2008.
- Y. Chincholkar and A. Kumar, “Traffic Sign Board Detection And Recognition For Autonomous Vehicles And Driver Assistance Systems”, ICTACT Journal on Image and Video Processing, Vol. 9, No. 3, pp. 1954-1959, 2019.
- P. Mohanaiah, P. Sathyanarayana and L. Guru Kumar, “Image Texture Feature Extraction using GLCM”, International Journal of Scientific and Research, Vol. 3, No. 5, pp. 1-8, 2013
- S. Patel, P. Trivedi, V. Gandhi and G. Prajapati, “Object Detection by Colour Threshold Method”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 4, No. 10, pp. 1-9, 2013.
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