DocumentCode :
1367373
Title :
Multidimensional orientation estimation with applications to texture analysis and optical flow
Author :
Bigun, Josef ; Granlund, Gosta H. ; Wiklund, Johan
Author_Institution :
Lab. de Traitement des Signaux, Ecole Polytech. Federale de Lausanne, Switzerland
Volume :
13
Issue :
8
fYear :
1991
fDate :
8/1/1991 12:00:00 AM
Firstpage :
775
Lastpage :
790
Abstract :
The problem of detection of orientation in finite dimensional Euclidean spaces is solved in the least squares sense. The theory is developed for the case when such orientation computations are necessary at all local neighborhoods of the n-dimensional Euclidean space. Detection of orientation is shown to correspond to fitting an axis or a plane to the Fourier transform of an n-dimensional structure. The solution of this problem is related to the solution of a well-known matrix eigenvalue problem. The computations can be performed in the spatial domain without actually doing a Fourier transformation. Along with the orientation estimate, a certainty measure, based on the error of the fit, is proposed. Two applications in image analysis are considered: texture segmentation and optical flow. The theory is verified by experiments which confirm accurate orientation estimates and reliable certainty measures in the presence of noise. The comparative results indicate that the theory produces algorithms computing robust texture features as well as optical flow
Keywords :
Fourier transforms; computer vision; least squares approximations; Fourier transform; certainty measure; computer vision; finite dimensional Euclidean spaces; image analysis; least squares approximations; multidimensional orientation estimation; optical flow; orientation estimate; spatial domain; texture analysis; texture segmentation; Eigenvalues and eigenfunctions; Fourier transforms; Image motion analysis; Image segmentation; Image texture analysis; Least squares methods; Multidimensional systems; Optical noise; Optical sensors; Reliability theory;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.85668
Filename :
85668
Link To Document :
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