International Journal of Computational Intelligence Systems

Volume 2, Issue 3, December 2009, Pages 168 - 183

Anisotropic Wavelet-Based Image Nearness Measure

Authors
James F. Peters, Leszek Puzio
Corresponding Author
James F. Peters
Available Online 1 December 2009.
DOI
https://doi.org/10.2991/ijcis.2009.2.3.1How to use a DOI?
Keywords
Anisotropic wavelets, Image resemblance, Near sets, Image nearness measure
Abstract
The problem considered in this article is how to solve the image correspondence problem in cases where it is important to measure changes in the contour, position, and spatial orientation of bounded regions. This article introduces a computational intelligence approach to the solution of this problem with anisotropic (direction dependent) wavelets and a tolerance near set approach to detecting similarities in pairs of im- ages. Near sets are a recent generalization of rough sets introduced by Z. Pawlak during the early 1980s. Near sets resulted from a study of the perceptual basis for rough sets. Pairs of sets containing objects with similar descriptions are known as near sets. The proposed wavelet-based image nearness measure is com- pared with F. Hausdorff and P. Mahalanobis image distance measures. The results of three wavelet-based image resemblance measures for several well-known images, are given. A direct benefit of this research is an effective means of grouping together (classifying) images that correspond to each other relative to minuscule similarities in the contour, position, and spatial orientation of bounded regions in the images, especially in videos containing image sequences showing varied object movements. The contribution of this article is the introduction of an anisotropic wavelet-based measure of image resemblance using a near set approach.
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This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
2 - 3
Pages
168 - 183
Publication Date
2009/12
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.2009.2.3.1How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - James F. Peters
AU  - Leszek Puzio
PY  - 2009
DA  - 2009/12
TI  - Anisotropic Wavelet-Based Image Nearness Measure
JO  - International Journal of Computational Intelligence Systems
SP  - 168
EP  - 183
VL  - 2
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2009.2.3.1
DO  - https://doi.org/10.2991/ijcis.2009.2.3.1
ID  - Peters2009
ER  -