Open Access
MATEC Web of Conferences
Volume 61, 2016
The International Seminar on Applied Physics, Optoelectronics and Photonics (APOP 2016)
Article Number 02007
Number of page(s) 6
Section Chapter 2 Electronic Technology and Electrical Engineering
Published online 28 June 2016
  1. Hsu-Yung Cheng, Chih-Chia Weng, and Yi-Ying Chen, —Vehicle Detection in Aerial Surveillance Using Dynamic Bayesian Networks, IEEE Trans. Image Process., vol. 21, no. 4, pp. 2152–2159, Apr. 2012. [CrossRef] [Google Scholar]
  2. Barilla-Perez, M. E. (2008). Colour-based Texture Image Segmentation, PhD thesis, University of Birmingham. [Google Scholar]
  3. Koller D, Weber J. Huang T. Malik J. Ogasawara G. Rao B. Russell S. Towards robust automatic traffic scene analysis in real-time. in Proceedings of the 33rd IEEE Conference on Decision and Control (Cat. No.94CH3460-3). IEEE. Part vol.4, 1994. 1994. [Google Scholar]
  4. G. Wyszecki and W. S. Styles, “Color Science: Concepts and Methods, Quantitative Data and Formulae” (2nd edition New York: Wiley, 1982). [Google Scholar]
  5. R. S. Berns, “Principles of Color Technology” (3rd edition New York: Wiley, 2000). [Google Scholar]
  6. J. L. Vincent, “Morphological Grayscale Reconstruction in Image Analysis: Applications and Efficient Algorithms”, IEEE Transactions on Image Processing, vol. 2, pp. 176–201, 1993. [NASA ADS] [CrossRef] [Google Scholar]
  7. M. Sezgin and B. Sankur, “Survey over Image Thresholding Techniques and Quantitative Performance Evaluation”, Journal of Electronic Imaging, vol. 13, no. 1, pp. 146–168, Jan. 2004. [Google Scholar]
  8. N. R. Pal and D. Bhandari, “On Object Background Classification”, International Journal Syst. Science, vol. 23, no. 11, pp. 1903–1920, Nov. 1992. [CrossRef] [Google Scholar]
  9. F. Meyer, “Color image segmentation”, Proceedings of 4th International Conference on Image Processing, pp. 523–548, 1992. [Google Scholar]
  10. [Google Scholar]
  11. Shalinee Patel, Pinal Trivedi, and Vrundali Gandhi, “2D Basic Shape Detection Using Region Properties”, International Journal of Engineering Research & Technology, vol. 2, no. 5, pp. 1147–1153, May 2013. [Google Scholar]
  12. Zehang Sun, George Bebis and Ronald Miller, —Quantized Wavelet Features and Support Vector Machines for On-Road Vehicle Detection, II Computer Vision Laboratory, Department of Computer Science, University of Nevada. [Google Scholar]
  13. C. Papageorgiou and T. Poggio, —A trainable system for object detection,” International Journal of Computer Vision, vol. 38, no. 1, pp. 15–33, 2000. [CrossRef] [Google Scholar]
  14. H. Schneiderman, A statistical approach to 3D object detection applied to faces and cars. CMU-RI-TR-00-06, 2000. [Google Scholar]
  15. G. Garcia, G. Zikos, and G. Tziritas, —Wavelet packet analysis for face recognition,” Image and Vision Computing, vol. 18, pp. 289–297, 2000. [Google Scholar]
  16. C. Jacobs, A. Finkelstein and D. Salesin, “Fast multiresolution image querying”, Proceedings of SIGGRAPH, pp. 277–286, 1995. [Google Scholar]
  17. R. C. Gonzalez and R. E.Woods, Digital Image Processing, Third Edition, 2008. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.