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Abstract Details
Activity Number:
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510
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #301961 |
Title:
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Feature-Based Image Registration Using Nondegenerate Pixels
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Author(s):
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Chen Xing*+ and Peihua Qiu
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Companies:
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University of Minnesota at Twin Cities and University of Minnesota at Twin Cities
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Address:
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471 Ford Hall, Minneapolis, MN, 55455,
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Keywords:
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image registration ;
degenerate ;
local smoothing ;
image matching ;
feature extraction ;
thin plate splines
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Abstract:
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Image registration (IR) aims to geometrically match one image to another. It is extensively used in many imaging applications. Among many existing IR methods, one widely used group of methods are feature-based. By a feature-based method, a number of relevant image features are first extracted from the two images, respectively, and then a geometric matching transformation is found to best match the two sets of features. However, proper identification and extraction of image features turns out to be a challenging task. Generally speaking, a good image feature extraction method should have the following two properties: (i) the identified image features should provide us enough information to approximate the geometric matching transformation accurately, and (ii) they should be easy to identify by a computer algorithm so that the entire feature extraction procedure is computer automatic. In this paper, a new type of image features is studied, which has the two properties described above. Together with the widely used thin plate spline (TPS) geometric transformation model, it is shown in the paper that our feature-based IR method works effectively in various cases.
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