%0 Journal Article
%T A Robust Template Matching Algorithm Based on Reducing Dimensions
%A Y. M. Fouda
%J Journal of Signal and Information Processing
%P 109-122
%@ 2159-4481
%D 2015
%I Scientific Research Publishing
%R 10.4236/jsip.2015.62011
%X Template matching is a fundamental problem
in pattern recognition, which has wide applications, especially in industrial
inspection. In this paper, we propose a 1-D template matching algorithm which
is an alternative for 2-D full search block matching algorithms. Our approach
consists of three steps. In the first step the images are converted from 2-D
into 1-D by summing up the intensity values of the image in two directions
horizontal and vertical. In the second step, the template matching is performed
among 1-D vectors using the similarity function sum of square difference.
Finally, the decision will be taken based on the value of similarity function.
Transformation template image and sub-images in the source image from 2-D grey
level information into 1-D information vector reduce the dimensionality of the
data and accelerate the computations. Experimental results show that the
computational time of the proposed approach is faster and performance is better
than three basic template matching methods. Moreover, our approach is robust to
detect the target object with changes of illumination in the template also when
the Gaussian noise added to the source image.
%K Image Processing
%K Template Matching
%K Vector Sum
%K Sum of Square Difference
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=55307