liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Hierarchical curvature estimation in computer vision
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
1991 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

This thesis concerns the estimation and description of curvature for computer vision applications. Different types of multi-dimensional data are considered: images (2D); volumes (3D); time sequences of images (3D); and time sequences of volumes (4D).

The methods are based on local Fourier domain models and use local operations such as filtering. A hierarchical approach is used. Firstly, the local orientation is estimated and represented with a vector field equivalent description. Secondly, the local curvature is estimated from the orientation description. The curvature algorithms are closely related to the orientation estimation algorithms and the methods as a whole give a unified approach to the estimation and description of orientation and curvature. In addition, the methodology avoids thresholding and premature decision making.

Results on both synthetic and real world data are presented to illustrate the algorithms performance with respect to accuracy and noise insensitivity. Examples illustrating the use of the curvature estimates for tasks such as image enhancement are also included.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press , 1991. , 163 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 253
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-54887ISBN: 91-7870-797-8OAI: diva2:311049
Public defence
1991-09-13, 101, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Available from: 2010-04-19 Created: 2010-04-19 Last updated: 2010-05-27Bibliographically approved

Open Access in DiVA

Hierarchical curvature estimation in computer vision(28444 kB)438 downloads
File information
File name FULLTEXT02.pdfFile size 28444 kBChecksum SHA-512
Type fulltextMimetype application/pdf
Cover(413 kB)15 downloads
File information
File name COVER01.pdfFile size 413 kBChecksum SHA-512
Type coverMimetype application/pdf

By organisation
Computer VisionThe Institute of Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 439 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 142 hits
ReferencesLink to record
Permanent link

Direct link