Title
Direct representation and detecting of multi-scale, multi-orientation fields using local differentiation filters.
Abstract
A computational framework is provided for representing and detecting multiple orientation fields from a set of local differentiation filters such as multiscale Gaussian derivatives. The representation is direct and closed-form, i.e., it is not necessary to steer the filters in order to detect multiple orientations. They can be estimated in a single-shot manner by solving algebraic equations. The filter does not need to be strongly tuned to orientations, since the derived algorithm does not suffer from the problem of interference between signal components of the multiple orientations. The capability of extracting the characteristic image structures of different scales is demonstrated by simulation. These advantages are accomplished by using the principle of superposition.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Year
DOI
Venue
1993
10.1109/CVPR.1993.341082
CVPR
Keywords
Field
DocType
filtering and prediction theory,image processing,algebraic equations,characteristic image structure extraction,direct closed-form representation,field detection,local differentiation filters,multiscale Gaussian derivatives,multiscale multiorientation field representation,single-shot estimation,superposition
Gaussian derivatives,Computer vision,Superposition principle,Information processing,Motion detection,Direct representation,Computer science,Image processing,Algebraic equation,Artificial intelligence,Interference (wave propagation)
Conference
Volume
Issue
ISSN
1993
1
1063-6919
Citations 
PageRank 
References 
5
0.50
0
Authors
2
Name
Order
Citations
PageRank
Masahiko Shizawa1247.67
Toshiki Iso2626.49