Robust and efficient image alignment based on relative gradient matching.

Full Abstract

In this paper, we present a robust image alignment algorithm based on matching of relative gradient maps. This algorithm consists of two stages; namely, a learning-based approximate pattern search and an iterative energy-minimization procedure for matching relative image gradient. The first stage finds some candidate poses of the pattern from the image through a fast nearest-neighbor search of the best match of the relative gradient features computed from training database of feature vectors, which are obtained from the synthesis of the geometrically transformed template image with the transformation parameters uniformly sampled from a given transformation parameter space. Subsequently, the candidate poses are further verified and refined by matching the relative gradient images through an iterative energy- minimization procedure. This approach based on the matching of relative gradients is robust against nonuniform illumination variations. Experimental results on both simulated and real images are shown to demonstrate superior efficiency and robustness of the proposed algorithm over the conventional normalized correlation method.

Learn Faster Today Improve your study skills

Author information

Author/s: Wei, Shou-Der (SD); Lai, Shang-Hong (SH);

Affiliation: Department of Computer Science, National Tsing-Hua University, Hsinchu, Taiwan. dr918308(-atsign-)cs.nthu.edu.tw

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society (IEEE Trans Image Process), published in United States. (Language: eng)

Reference: 2006-Oct; vol 15 (issue 10) : pp 2936-43

Dates: Created 2006/10/06; Completed 2006/11/20;

PMID: 17022260, status: MEDLINE (last retrieval date: 12/26/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

External Links for this article (including full text providers, if available):

Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.

This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.

MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms
Artificial Intelligence
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods

Image Interpretation, Computer-Assisted - methods
Information Storage and Retrieval - methods
Pattern Recognition, Automated - methods
Subtraction Technique

These are the highest related articles currently in the database:

Concurrent computation of attribute filters on shared memory parallel machines. 29 Sep 2008
Design of multimodal dissimilarity spaces for retrieval of video documents. 30 Aug 2008
Effective proximity retrieval by ordering permutations. 30 Aug 2008
Restoration of DWI data using a Rician LMMSE estimator. 29 Sep 2008
Script-independent text line segmentation in freestyle handwritten documents. 30 Jul 2008
Cost aggregation and occlusion handling with WLS in stereo matching. 30 Jul 2008
A discriminative kernel-based approach to rank images from text queries. 30 Jul 2008
Class-based feature matching across unrestricted transformations. 30 Aug 2008
Parametric image alignment using enhanced correlation coefficient maximization. 29 Sep 2008
Variational Bayesian image restoration based on a product of t-distributions image prior. 29 Sep 2008

See 100+ related articles.