15
IoT-Enabled Vision System for Detection of Tint Level
Bibliography
1. H. Zhiwei, L. Jilin and L. Peihong, New Method of Background Update for Video-based
Vehicle Detection, in 2004 IEEE Intelligent Transportation Systems Conference, Washington,
DC, pp. 582–584 (2004).
2. P. Arbeláez, M. Maire, C. Fowlkes and J. Malik, Contour Detection and Hierarchical Image
Segmentation, IEEE TPAMI, Vol. 33(5), pp. 898–916 (2011).
3. T. Ko, S. Soatto and D. Estrin, Background Subtraction on Distributions, Computer VisionECCV 2008, Lect. Notes Comput. Sci., Vol. 5304, pp. 276–289 (2008).
4. S.Y. Elhabian, K.M. El-Sayed and S.H. Ahmed, Moving Object Detection in Spatial Domain
using Background Removal Techniques—State-of-Art, Recent Patents Comput. Sci., Vol. 1(1),
pp. 32–54 (2008).
5. A. Elgammal, D. Harwood and L. Davis, Non-parametric Model for Background Subtraction,
ECCV-2000, Lect. Notes Comput. Sci., Vol. 1843, pp. 751–767 (2000).
6. P.W. Power and J.A. Schoonees, Understanding Background Mixture Models for Foreground
Segmentation, in Proceedings of Image and Vision Computing, University of Auckland,
Auckland, New Zealand, pp. 267–271 (2002).
7. C. Stauffer and W.E.L. Grimson, Adaptive Background Mixture Models for Real-Time Tracking,
Comput. Vision Pattern Recogn., Vol. 2, pp. 252–258 (1999).
8. A. Mittal and N. Paragios, Motion-Based Background Subtraction Using Adaptive Kernel
Density Estimation, in Proceedings of 2004 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition, Washington, DC, pp. 302–209 (2004).
9. X. Hao, H. Chen, Y. Yang, C. Yao, H. Yang and N. Yang, Occupant Detection through NearInfrared Imaging, Tamkang J. Sci. Eng., Vol. 14(3), pp. 275–283 (2011).
10. M.R.J. Baldock, A.J. McLean and C.N. Kloeden, Front Side Window Tinting Visual Light
Transmittance Requirements, CASR Report Series, CASR002, Centre for Automotive Safety
Research, The University of Adelaide, Adelaide, Australia (2004).
11. M.-Y. Ku, C.-C. Chiu, H.-T. Chen and S.-H. Hong, Visual Motorcycle Detection and Tracking
Algorithms, Wseas Trans. Electron., Vol. 5(4), pp. 121–131 (2008).
12. K. Ganesan, C. Kavitha, K. Tandon and R. Lakshmipriya, Traffic Surveillance Video Management
System, Int. J. Multimedia Appl., Vol. 2(4), pp. 28–36 (2010).
13. C.-C. Chiu, M.-R. Ku and C.-Y. Wang, Automatic Traffic Surveillance System for Vision Based
Vehicle Recognition and Tracking, J. Inform. Sci. Eng., Vol. 26(2), pp. 611–629 (2010).
14. J. Lee and M. Park, An Adaptive Background Subtraction Method Based on Kernel Density
Estimation, Sensors, Vol. 12, pp. 12279–12300 (2012).
15. A. Raju, G.S. Dwarakish and D.V. Reddy, A comparative Analysis of Histogram Equalization
Based Techniques for Contrast Enhancement and Brightness Preserving, Int. J. Signal Proc.
Image Proc. Pattern Recogn., Vol. 6(5), pp. 353–366 (2013).
16. L. Kabbai, A. Sghaier, D. Ali and M. Machhout, FPGA Implementation of Filtered Image Using
2D Gaussian Filter, Int. J. Adv. Comp. Sci. Apps., Vol. 7(7), pp. 514–520 (2016).
17. M.K. Kaushik and R. Kasyap, A Review Paper on Denosing Filter Using 2D Gaussian Smooth
Filter for Multimedia Application, Int. Res. J. Comp. Sci., Vol. 5(3), pp. 21–26 (2016).
18. A. Aslam, E. Khan and M.M. Sufyan Beg, Improved Edge Detection Algorithm for Brain
Tumor Segmentation, Procedia Comp. Sci., Vol. 58, pp. 430–437 (2015).
19. C. Jin, T. Chen and L. Ji, License Plate Recognition Based on Edge Detection Algorithm, in 2013
Ninth Int. Conf. on Intelligent Information Hiding and Multimedia Signal Processing, Beijing, China,
pp. 395–398 (2013).
20. M.M. Shidore and S.P. Narote, Number Plate Recognition for Indian Vehicles, Int. J. Comp. Sci.
Netw. Secur., Vol. 11(2), pp. 143–146 (2011).
21. Traffic Surveillance Video Management System, Int. J. Multimedia Appl., Vol. 2(4), (2010).
IoT-Enabled Vision System for Detection of Tint Level
Bibliography
1. H. Zhiwei, L. Jilin and L. Peihong, New Method of Background Update for Video-based
Vehicle Detection, in 2004 IEEE Intelligent Transportation Systems Conference, Washington,
DC, pp. 582–584 (2004).
2. P. Arbeláez, M. Maire, C. Fowlkes and J. Malik, Contour Detection and Hierarchical Image
Segmentation, IEEE TPAMI, Vol. 33(5), pp. 898–916 (2011).
3. T. Ko, S. Soatto and D. Estrin, Background Subtraction on Distributions, Computer VisionECCV 2008, Lect. Notes Comput. Sci., Vol. 5304, pp. 276–289 (2008).
4. S.Y. Elhabian, K.M. El-Sayed and S.H. Ahmed, Moving Object Detection in Spatial Domain
using Background Removal Techniques—State-of-Art, Recent Patents Comput. Sci., Vol. 1(1),
pp. 32–54 (2008).
5. A. Elgammal, D. Harwood and L. Davis, Non-parametric Model for Background Subtraction,
ECCV-2000, Lect. Notes Comput. Sci., Vol. 1843, pp. 751–767 (2000).
6. P.W. Power and J.A. Schoonees, Understanding Background Mixture Models for Foreground
Segmentation, in Proceedings of Image and Vision Computing, University of Auckland,
Auckland, New Zealand, pp. 267–271 (2002).
7. C. Stauffer and W.E.L. Grimson, Adaptive Background Mixture Models for Real-Time Tracking,
Comput. Vision Pattern Recogn., Vol. 2, pp. 252–258 (1999).
8. A. Mittal and N. Paragios, Motion-Based Background Subtraction Using Adaptive Kernel
Density Estimation, in Proceedings of 2004 IEEE Computer Society Conference on Computer
Vision and Pattern Recognition, Washington, DC, pp. 302–209 (2004).
9. X. Hao, H. Chen, Y. Yang, C. Yao, H. Yang and N. Yang, Occupant Detection through NearInfrared Imaging, Tamkang J. Sci. Eng., Vol. 14(3), pp. 275–283 (2011).
10. M.R.J. Baldock, A.J. McLean and C.N. Kloeden, Front Side Window Tinting Visual Light
Transmittance Requirements, CASR Report Series, CASR002, Centre for Automotive Safety
Research, The University of Adelaide, Adelaide, Australia (2004).
11. M.-Y. Ku, C.-C. Chiu, H.-T. Chen and S.-H. Hong, Visual Motorcycle Detection and Tracking
Algorithms, Wseas Trans. Electron., Vol. 5(4), pp. 121–131 (2008).
12. K. Ganesan, C. Kavitha, K. Tandon and R. Lakshmipriya, Traffic Surveillance Video Management
System, Int. J. Multimedia Appl., Vol. 2(4), pp. 28–36 (2010).
13. C.-C. Chiu, M.-R. Ku and C.-Y. Wang, Automatic Traffic Surveillance System for Vision Based
Vehicle Recognition and Tracking, J. Inform. Sci. Eng., Vol. 26(2), pp. 611–629 (2010).
14. J. Lee and M. Park, An Adaptive Background Subtraction Method Based on Kernel Density
Estimation, Sensors, Vol. 12, pp. 12279–12300 (2012).
15. A. Raju, G.S. Dwarakish and D.V. Reddy, A comparative Analysis of Histogram Equalization
Based Techniques for Contrast Enhancement and Brightness Preserving, Int. J. Signal Proc.
Image Proc. Pattern Recogn., Vol. 6(5), pp. 353–366 (2013).
16. L. Kabbai, A. Sghaier, D. Ali and M. Machhout, FPGA Implementation of Filtered Image Using
2D Gaussian Filter, Int. J. Adv. Comp. Sci. Apps., Vol. 7(7), pp. 514–520 (2016).
17. M.K. Kaushik and R. Kasyap, A Review Paper on Denosing Filter Using 2D Gaussian Smooth
Filter for Multimedia Application, Int. Res. J. Comp. Sci., Vol. 5(3), pp. 21–26 (2016).
18. A. Aslam, E. Khan and M.M. Sufyan Beg, Improved Edge Detection Algorithm for Brain
Tumor Segmentation, Procedia Comp. Sci., Vol. 58, pp. 430–437 (2015).
19. C. Jin, T. Chen and L. Ji, License Plate Recognition Based on Edge Detection Algorithm, in 2013
Ninth Int. Conf. on Intelligent Information Hiding and Multimedia Signal Processing, Beijing, China,
pp. 395–398 (2013).
20. M.M. Shidore and S.P. Narote, Number Plate Recognition for Indian Vehicles, Int. J. Comp. Sci.
Netw. Secur., Vol. 11(2), pp. 143–146 (2011).
21. Traffic Surveillance Video Management System, Int. J. Multimedia Appl., Vol. 2(4), (2010).