USING GRA FOR 2D INVARIANT OBJECT RECOGNITION

T.-H. Sun, J. C. Liu, C.-H. Tang, F.-C. Tien

Abstract

Invariant features are vital to domain of pattern recognition. This research develops a vision-based invariant recognizer for 2D object. We perform a recognition method which adopted KRA invariant feature extractor and used grey relational analysis. The feature extraction is to derive translation, rotation, and scaling-free features through the sequential boundary and is described with its K-curvature. Our work represents the object profile with the K-curvature to obtain the position invariant property; and then the transformation of autocorrelation is to ensure orientation-invariant property. Experimental also reveals that proposed method with either GRA or MD methods offers distinctiveness and effectiveness for part recognition.

References

  1. Cao, W., Hao, F., & Wang, S. (2004). The application of DBF neural networks for object recognition. Information Sciences, 160, 153-160.
  2. Chang, K.-C., Yeh, M.-F. (2005). Grey relational analysis based approach for data clustering, IEE Proc.- Vis. Image Signal Process 152 (2), April 2005, 165-172.
  3. Chen, C.-M.; Chen, Y.-Y., Liu, C.-Y. (2007). Learning Performance Assessment Approach Using Web-Based Learning Portfolios for E-learning Systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 37 (6), 1349 - 1359.
  4. Deng, L.-L. (1982). Control problems of grey systems, Systems and Control Letters 5(1), 288-294.
  5. Deng, J.-L. (1989). Introduction to grey system theory, Journal of Grey System 1, 1-24.
  6. Jiang, B.C., Tasi, S.L, Wang, C.C. (2002), Machine vision-based grey relational theory applied to IC marking inspection, IEEE Transaction on Semiconductor Manufacturing 15 (4), 531-530.
  7. Jones, G., III, & Bhanu, B. (2001). Recognizing articulated objects in SAR images. Pattern Recognition, 34, 469-485.
  8. Khalil, M. I., & Bayoumi, M. M. (2002a). Affine invariants for object recognition using the wavelet transform. Pattern Recognition Letters 23, 57-72.
  9. Khalil, M. I., & Bayoumi, M. M. (2002b). Invariant 2D object recognition using the wavelet modulus maxima. Pattern Recognition Letters, 21, 863-872.
  10. Li, W., and Lee, T. (2004). Projective invariant object recognition by a Hopfield network. Neurocomputing, 30, 1-18.
  11. Popovici, V., & Thiran, J.-P. (2004). Pattern recognition using higher-order local autocorrelation coefficients. Pattern Recognition Letters, 25, 1107-1113.
  12. Rosenfeld, A., Johnson, E. (1973), Angle detection on digital curves, IEEE Transactions on Computers C-22, 875-878.
  13. Sohn, K., Alexander, W.E., Kim, J.H., Snyder, W.E. (1994) A constrained regularization approach to robust corner detection. IEEE Transactions on Systems, Man, and Cybernetics. 24 (5), 820-828.
  14. Lursinsap, C. (2006). A new feature extractor invariant to intensity, rotation, and scaling of color images. Information Sciences, 176, 2097-2119.
  15. Sun, T.-H. (2008). K-cosine corner detection. Journal of Computers. In press.
  16. Hsieh, K. H. (2004). Automated visual inspection of microdrill for PCB production. International Journal of Production Research, 15(42), 2477-2495.
  17. Tsai, D.M. (1997). Boundary-based corner detection using neural networks, Pattern Recognition 30 (1), 85-97.
  18. Tsai, D. M., Hou, H.-T., & Su, H.-J. (1999). Boundarybased corner detection using eigenvalues of covariance matrices. Pattern Recognition Letters, 20, 31-40.
  19. Bennamoun, M. (2007). Complete invariants for robust face recognition. Pattern Recognition, 40, 1579-1591.
  20. Zhang, J, Zhang, X, Krim, H., Walter, G.G. (2003), Object representation and recognition in shape spaces, Pattern Recognition 36, 1143-1154.
Download


Paper Citation


in Harvard Style

Sun T., Liu J., Tang C. and Tien F. (2009). USING GRA FOR 2D INVARIANT OBJECT RECOGNITION . In Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-85-2, pages 109-112. DOI: 10.5220/0001958101090112


in Bibtex Style

@conference{iceis09,
author={T.-H. Sun and J. C. Liu and C.-H. Tang and F.-C. Tien},
title={USING GRA FOR 2D INVARIANT OBJECT RECOGNITION},
booktitle={Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2009},
pages={109-112},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001958101090112},
isbn={978-989-8111-85-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - USING GRA FOR 2D INVARIANT OBJECT RECOGNITION
SN - 978-989-8111-85-2
AU - Sun T.
AU - Liu J.
AU - Tang C.
AU - Tien F.
PY - 2009
SP - 109
EP - 112
DO - 10.5220/0001958101090112