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Medical Image Registration using Cauchy-Schwarz Inequality via Template Matching
Author(s) -
Sunanda Gupta,
S. K. Chakarvarti,
Zaheerudin
Publication year - 2016
Publication title -
american journal of algorithms and computing
Language(s) - English
Resource type - Journals
eISSN - 2162-9900
pISSN - 2162-9897
DOI - 10.7726/ajac.2016.1002
Subject(s) - cauchy distribution , cauchy–schwarz inequality , mathematics , matching (statistics) , artificial intelligence , image registration , image (mathematics) , image matching , inequality , computer vision , computer science , mathematical analysis , statistics
Template matching is one of the areas of profound interest in image processing and is a technique in digital image processing to find small parts of an image which matches a template image. Template can be considered a sub-image from the reference image, and the image can be considered as a sensed image. The objective is to find the measure of the degree of similarity between an examined image and template, and it establishes the correspondence between the examined image and template image. In this paper, an algorithm providing normalized cross correlation (NCC) for template matching is developed and implemented using MATLAB. The experimental results are presented and found that proposed algorithm is a robust method for the similarity measure.

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