STATISTICAL TECHNIQUES FOR EDGE DETECTION IN HISTOLOGICAL IMAGES

D. Svoboda, I. A. Williams†, N. Bowring†, E. Guest

2006

Abstract

A review of the statistical techniques available for performing edge detection on histological images is presented. The tests under review include the Student’s T Test, the Fisher test, the Chi Square test, the Kolmogorov Smirnov test, and the Mann Whitney U test. All utilize a novel two sample edge detector to compare the statistical properties of two image regions surrounding a central pixel. The performance of the statistical tests is compared using histological biomedical images on which traditional gradient based techniques are not as successful, therefore giving an overall review of the methods, and results. Comparisons are also made to the more traditional Canny and Sobel, edge detection filters. The results show that in the presence of noise and clutter in histological images both parametric and non-parametric statistical tests compare well robustly extracting edge information on a series images.

References

  1. Beauchemin, M., Thomson, K. P. B., and Edwards, G. (1998). On nonparametric edge detection in multilook sar images. IEEE Transactions on GRS, 36(5):1826- 1829.
  2. Bovik, A. C., Huang, T. S., and Jr, D. C. M. (1986). Nonparametric tests for edge detection in noise. Pattern Recognition, 19(3):209-219.
  3. Bowring, N. J., Guest, E., Twigg, P., Fan, Y., and Gadsby, D. (2004). A new statistical method for edge detection on textured and cluttered images. In 4th IASTED VIIP Conf., pages 435-440.
  4. Brune, M., Bard, J., Dubreuil, C., Guest, E., Hill, W., Kaufman, M., Stark, M., Davidson, D., and Baldock, R. (1999). A three-dimensional model of the mouse at embryonic day 9. 216(2):457-468.
  5. Canny, J. (1986). A computational approach to edge detection. IEEE T-PAMI, 8:769-698.
  6. de Souza, P. (1983). Edge detection using sliding statistical tests. CVGIP, 23(1):1-14.
  7. Fesharaki, M. N. and Hellestrand, G. R. (1994). A new edge detection algorithm based on a statistical approach. In ICSIPNN 7894, pages 21-24. IEEE.
  8. Hou, Z. (2003). Robust edge detection. Pattern Recognition, 36(9):2083-2091.
  9. Huang, J. S. and Tseng, D. H. (1988). Statistical theory of edge detection. CVGIP, 34(3):337-346.
  10. Kundu, A. (1990). Robust edge detection. Pattern Recognition, 23(5):423-440.
  11. Lim, D. H. and Jan, S. J. (2002). Comparison of two-sample tests for edge detection in noisy images. Statistician, 51(1):21-30.
  12. Lim, D. H. and Jan, S. J. (2006). Robust edge detection in noisy images. Computational Statistics and Data Analysis, 50(3):803-812.
  13. Perona, P. and Malik, J. (1990). Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Inteligence, 12(7):629-639.
  14. Pratt, W. K. (1991). Digital Image Processing. ISBN: 0-471-37407-5.
  15. Smith, S. and Brady, J. (1997). Susan - a new approach to low level image processing. IJCV, 23(1):45-78.
  16. S?onka, M., Hlavác?, V., and Boyle, R. (1986). Image Processing Analysis and Machine Vision. Chapman and Hall Publishing. London.
  17. Williams, I., Bowring, N. J., Guest, E., Twigg, P., Fan, Y., and Gadsby, D. (2005). A combined statistical/neural network multi-scale edge detector. In 5th IASTED VIIP Conf. ISBN: 0-88986-528-0, ref: 480-266.
Download


Paper Citation


in Harvard Style

Svoboda D., A. Williams† I., Bowring† N. and Guest E. (2006). STATISTICAL TECHNIQUES FOR EDGE DETECTION IN HISTOLOGICAL IMAGES . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 972-8865-40-6, pages 457-462. DOI: 10.5220/0001377904570462


in Bibtex Style

@conference{visapp06,
author={D. Svoboda and I. A. Williams† and N. Bowring† and E. Guest},
title={STATISTICAL TECHNIQUES FOR EDGE DETECTION IN HISTOLOGICAL IMAGES},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2006},
pages={457-462},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001377904570462},
isbn={972-8865-40-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - STATISTICAL TECHNIQUES FOR EDGE DETECTION IN HISTOLOGICAL IMAGES
SN - 972-8865-40-6
AU - Svoboda D.
AU - A. Williams† I.
AU - Bowring† N.
AU - Guest E.
PY - 2006
SP - 457
EP - 462
DO - 10.5220/0001377904570462