Recognition of blurred images by the method of moments

The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on image processing 1996-03, Vol.5 (3), p.533-538
Main Authors: Flusser, J., Suk, T., Saic, S.
Format: Article
Language:English
Subjects:
Applied sciences
Exact sciences and technology
Flowcharts
Image databases
Image processing
Image recognition
Image restoration
Information, signal and communications theory
Layout
Moment methods
Robustness
Signal processing
Spatial databases
Streaming media
Telecommunications and information theory
Wiener filter
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The article is devoted to the feature-based recognition of blurred images acquired by a linear shift-invariant imaging system against an image database. The proposed approach consists of describing images by features that are invariant with respect to blur and recognizing images in the feature space. The PSF identification and image restoration are not required. A set of symmetric blur invariants based on image moments is introduced. A numerical experiment is presented to illustrate the utilization of the invariants for blurred image recognition. Robustness of the features is also briefly discussed.
ISSN:1057-7149
1941-0042
DOI:10.1109/83.491327