Детектирование и распознавние объектов в системах автомобильной безопасности на основе фрактального анализа
Минаев Е.Ю., Никоноров А.В.

Аннотация:
В работе рассматриваются задачи детектирования бликов артефактов, затрудняющих работу видеосистем обеспечения безопасности на транспорте, а также задачи распознавания дорожных знаков в видеосистемах. Предложены алгоритмы решения указанных задач на основе методов фрактального анализа. Экспериментально показана эффективность разработанных алгоритмов детектирования в сравнении с алгоритмами на основе метода активных контуров.

Abstract:
The paper considers detection of artifacts in CCTV systems and recognition of the traffic signs. We propose the algorithms based on the fractal analysis to solve these problems. Proposed algorithm of artifact detection uses the fractal dimension as a shape feature of the artifact. Recognition algorithm is based on the iterative functions systems and comparison of its attractors. The efficiency of the proposed approaches was proved experimentally. Proposed algorithms are robust to the most of the image distortion such as scaling, rotation, and shift in the wide range of distortion intensity.

Ключевые слова :
системы видеонаблюдения, системы автобезопасности, распознавание образов, детектирование артефактов, фрактальная размерность, система итерированных функций.

Key words:
Driver assistance systems, CCTV systems, pattern recognition, artifacts detection, fractal dimension, iterative functions system.

Литература:

  1. Minaev, E. Effective Algorithms of Flare Detection with Analysis of the Shape in Real Time Video Surveillance Systems / E. Minaev, A. Nikonorov, P. Yakimov// Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications. – 2011. – Vol. 21(2). – P. 407-410.
  2. Minaev, E. Fractal Methods for Recognition of Compact Artifacts in Color Images / E. Minaev, A. Nikonorov //  Proceedings of  8th Open German-Russian Workshop “Pattern Recognition and Image Understanding”, Nizhny Novgorod. – 2011. – P. 198-201.
  3. Crownover, R.M. Indroduction to fractals and chaos / Jones & Bartett Publisher. – 1995. – 308 p.
  4. Bibikov, S.A. Information technology of retouching of point-like artefacts on color images / S.A.Bibikov, A.V. Nikonorov, V.A. Fursov// Proceedings of the IASTED ACIT 2010, June 2010, Novosibirsk, Russia. – 2010. – P. 123-126.
  5. Ihara, A. Improvement in the accuracy of matching by different feature subspaces in traffic sign recognition / A. Ihara, H. Fujiyoshi, M. Takaki, H. Kumon, Y. Tamatsu // IEEJ Trans. on Electronics, Information and Systems. – 2009. – N 129 (5). – P. 893-900.
  6. Lorsakul, A. Traffic Sign Recognition for Intelligent Vehicle Driver Assistance System Using Neural Network on OpenCV / A. Lorsakul, J. Suthakorn // Proc. of the 4th Int. Con. on Ubiquitous Robots and Ambient Intelligence. – 2007. – P. 279- 284.         
  7. Neil, G. Shape Recognition Using a Novel Fractal Technique / G. Neil, K. M. Curtis, M. P. Craven // Proc. of the IEEE Int’l Conf. on Electronics, Circuits and Systems. – 1996. – Vol. 2. – P. 724-727.
  8. Abate, A.F. 2D and 3D face recognition: a survey / A.F. Abate, M. Nappi, D. Riccio, G. Sabatino // Pattern Recognition Lett. – 2007. – Vol. 28 (14) – P. 1885-1906.
  9. Tan, T. Face recognition using the weighted fractal neighbor distance / T. Tan, H. Yan // Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on. – 2005. – Vol. 35, – P. 576-582.
  10. Tan, T.  Face recognition by fractal transformations / T. Tan, H. Yan // In Pr c. IEEE ICASSP. – 1999. – P. 3537-3540.
  11. Neil, G. Scale and Rotationally Invariant Object Recognition Using Fractal Transformations / G. Neil, K. M. Curtis // IEEE ICASSP. – 1996. – Vol. 6, – P. 3458-3461.
  12. Kunwar, R. Online handwriting recognition of Tamil script using Fractal geometry / R. Kunwar, A. G. Ramakrishnan // Proc. of 2011 International Conference on Document Analysis and Recognition, IEEE. – 2011.  –  P. 1389-1393.
  13. Мурашов, Д.М. Метод автоматизированной сегментации изображений цитологических препаратов на основе модели активного контура / Д.М. Мурашов // ТРУДЫ МФТИ. – 2009. – Т. 1, № 1. – С. 80-89.
  14. Bibikov, S.A. Detection and Color Correction of Artifacts in Digital Images / S.A.Bibikov, A.V. Nikonorov, V.A. Fursov, P.Y. Yakimov,  R.K. Zakharov// Optoelectronics, Instrumentation and Data Processing, Springer. – 2011. – Vol. 47 (3) – P. 226-223.
  15. Fursov, V.A. Color images correction – using identification technique / S.A.Bibikov, A.V. Nikonorov, V.A. Fursov, P.Y. Yakimov, E. Minaev // Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications, Springer. – 2011. – Vol. 21(2) – P. 123-126.
  16. Tuytelaars, T. Local Invariant Feature Detectors: A Survey / T. Tuytelaars, K. Mikolajczyk // Foundations and Trends® in Computer Graphics and Vision. – 2008. – Vol. 3(3). – P. 177-280.

References:

  1. Minaev, E. Effective Algorithms of Flare Detection with Analysis of the Shape in Real Time Video Surveillance Systems / E. Minaev, A. Nikonorov, P. Yakimov// Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications. – 2011. – Vol. 21(2). – P. 407-410.
  2. Minaev, E. Fractal Methods for Recognition of Compact Artifacts in Color Images / E. Minaev, A. Nikonorov //  Proceedings of  8th Open German-Russian Workshop “Pattern Recognition and Image Understanding”, Nizhny Novgorod. – 2011. – P. 198-201.
  3. Crownover, R.M. Indroduction to fractals and chaos / Jones & Bartett Publisher. – 1995. – 308 p.
  4. Bibikov S.A. Information technology of retouching of point-like artefacts on color images / S.A.Bibikov, A.V. Nikonorov, V.A. Fursov// Proceedings of the IASTED ACIT 2010, June 2010, Novosibirsk, Russia. – 2010. – P. 123-126.
  5. Ihara, A. Improvement in the accuracy of matching by different feature subspaces in traffic sign recognition / A. Ihara, H. Fujiyoshi, M. Takaki, H. Kumon, Y. Tamatsu // IEEJ Trans. on Electronics, Information and Systems. – 2009. – N 129 (5). – P. 893-900.
  6. Lorsakul, A. Traffic Sign Recognition for Intelligent Vehicle Driver Assistance System Using Neural Network on OpenCV / A. Lorsakul, J. Suthakorn // Proc. of the 4th Int. Con. on Ubiquitous Robots and Ambient Intelligence. – 2007. – P. 279- 284.         
  7. Neil, G. Shape Recognition Using a Novel Fractal Technique / G. Neil, K. M. Curtis, M. P. Craven // Proc. of the IEEE Int’l Conf. on Electronics, Circuits and Systems. – 1996. – Vol. 2. – P. 724-727.
  8. Abate, A.F. 2D and 3D face recognition: a survey / A.F. Abate, M. Nappi, D. Riccio, G. Sabatino // Pattern Recognition Lett. – 2007. – Vol. 28 (14) – P. 1885-1906.
  9. Tan, T. Face recognition using the weighted fractal neighbor distance / T. Tan, H. Yan // Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on. – 2005. – Vol. 35. – P. 576-582.
  10. Tan, T.  Face recognition by fractal transformations / T. Tan, H. Yan // In Pr c. IEEE ICASSP. – 1999. – P. 3537-3540.
  11. Neil, G. Scale and Rotationally Invariant Object Recognition Using Fractal Transformations / G. Neil, K. M. Curtis // IEEE ICASSP. – 1996. – Vol. 6. – P. 3458-3461.
  12. Kunwar, R. Online handwriting recognition of Tamil script using Fractal geometry / R. Kunwar, A. G. Ramakrishnan // Proc. of 2011 International Conference on Document Analysis and Recognition, IEEE. – 2011.  –  P. 1389-1393.
  13. Murashov, D.M. Automated cytological specimen imagesegmentation technique based on the active contour model / D.M. Murashev // Proc. of Moscow Institute of Physics and Technology (State University). – M.: - 2009. – V. 1, N 1. – P. 80-89. – (in Russian).
  14. Bibikov, S.A. Detection and Color Correction of Artifacts in Digital Images / S.A.Bibikov, A.V. Nikonorov, V.A. Fursov, P.Y. Yakimov,  R.K. Zakharov// Optoelectronics, Instrumentation and Data Processing, Springer. – 2011. – Vol. 47 (3) – P. 226-223.
  15. Fursov, V.A. Color images correction – using identification technique / S.A.Bibikov, A.V. Nikonorov, V.A. Fursov, P.Y. Yakimov, E. Minaev // Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications, Springer. – 2011. – Vol. 21(2) – P. 123-126.
  16. Tuytelaars, T. Local Invariant Feature Detectors: A Survey / T. Tuytelaars, K. Mikolajczyk // Foundations and Trends® in Computer Graphics and Vision. – 2008. – Vol. 3(3),  P. 177-280.
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