Feature detection from local energy

A more general definition of features such as edges, shadows and bars is developed, based on an analysis of the phase of the harmonic components. These features always occur at points of maximum phase congruency, the type of feature depending on the value of the phase. Using the image itself and its...

Full description

Saved in:
Bibliographic Details
Published inPattern recognition letters Vol. 6; no. 5; pp. 303 - 313
Main Authors Morrone, M.C., Owens, R.A.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.12.1987
Elsevier
Subjects
Applied sciences
Artificial intelligence
Computer science; control theory; systems
Edge detection
energy
Exact sciences and technology
Hilbert transform
odd and even symmetric filters
Pattern recognition. Digital image processing. Computational geometry
phase
phase
Hilbert transform
odd and even symmetric filters
Edge detection
energy
Image processing
Filter
Algorithm
Hilbert transformation
Online AccessGet full text

Cover

More Information
Summary:A more general definition of features such as edges, shadows and bars is developed, based on an analysis of the phase of the harmonic components. These features always occur at points of maximum phase congruency, the type of feature depending on the value of the phase. Using the image itself and its Hilbert transform, a local energy function is defined and it is shown that the local maxima of this energy function occur at points of maximum phase congruency.
ISSN:0167-8655
1872-7344
DOI:10.1016/0167-8655(87)90013-4