Abstract
A method to automatically select locally appropriate scales for feature detection, proposed by Lindeberg [8], [9], involves choosing a so-called γ-parameter. The implications of the choice of γ-parameter are studied and it is demonstrated that different values of γ can lead to qualitatively different features being detected. As an example the range of γ-values is determined such that a second derivative of Gaussian filter kernel detects ridges but not edges. Some results of this relatively simple ridge detector are shown for two-dimensional images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
D. Eberly. Ridges in Image and Data Analysis. Computational Imaging and Vision. Kluwer Academic Publishers, 1996.
W.T. Freeman and E.H. Adelson. The design and use of steerable filters. IEEE PAMI, 13(9):891–906, 1991.
D. Fritsch, S. Pizer, B. Morse, D. Eberly, and A. Liu. The multiscale medial axis and its applications in image regestration. Pattern Recognition Letters, 15:445–452, 1994.
J.J. Koenderink and A. van Doorn. Two-plus-one-dimensional differential geometry. Pattern Recognition Letters, 15(5):439–444, 1994.
T.M. Koller. From Data to Information: Segmentation, Description and Analysis of the Cerebral Vascularity. PhD thesis, Swiss Federal Institute of Technology, Zürich, 1995.
T.M. Koller, G. Gerig, G. Szekely, and D. Dettwiler. Multiscale detection of curvilinear structures in 2d and 3d medical images. In Fifth International Conference on Computer Vision ICCV 95, pages 864–869, Cambridge, MA, USA, 1995.
Axel F. Korn. Toward a symbolic representation of intensity changes in images. IEEE PAMI, 10(5):610–625, 1988.
T. Lindeberg. On scale selection for differential operators. In K. Heia, A. Hægdra, and B. Braathen, editors, 8th Scandinavian Conference on Image Analysis, pages 857–866, Tromsæ, Norway, 1993.
T. Lindeberg. Edge detection and ridge detection with automatic scale selection. International Journal of Computer Vision, 30(2):117–156, 1998.
C. Lorenz, I.-C. Carlsen, T.M. Buzug, C. Fassnacht, and J. Weese. A multiscale line filter with automatic scale selection based on the hessian matrix for medical image segmentation. In B. ter Haar Romeny, L. Florack, J. Koenderink, and M. Viergever, editors, Scale-space theory in Computer Vision, ScaleSpace’ 97, volume 1252 of Lecture Notes in Computer Science. Springer, 1997.
P. Majer. A Statistical Approach to Feature Detection and Scale Selection in Images. PhD thesis, University of Göttingen, 2000.
S. Pizer, D. Eberly, B. Morse, and D. Fritsch. Zoom-invariant figural shape: the mathematics of cores. Computer Vision and Image Understanding, 69:55–71, 1998.
S.M. Pizer, C.A. Burbeck, J.M. Coggins, D. Fritsch, and B. Morse. Object shape before boundary shape: Scale-space medial axis. J. Math. Im. Vis., 4:303–313, 1994.
J. Staal, S. Kalitzin, B. ter Haar Romeny, and M. Viergewer. Detection of critical structures in scale space. In M. Nielsen, P. Johansen, O. Olsen, and J. Weickert, editors, Scale-Space Theories in Computer Vision, 1999.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Majer, P. (2001). The Influence of the γ-Parameter on Feature Detection with Automatic Scale Selection. In: Kerckhove, M. (eds) Scale-Space and Morphology in Computer Vision. Scale-Space 2001. Lecture Notes in Computer Science 2106, vol 2106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47778-0_21
Download citation
DOI: https://doi.org/10.1007/3-540-47778-0_21
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42317-1
Online ISBN: 978-3-540-47778-5
eBook Packages: Springer Book Archive