  Template matching is a basic method in image analysis to extract useful
information from images. In this paper, we suggest a new method for pattern
matching. Our method transform the template image from two dimensional image
into one dimensional vector. Also all sub-windows (same size of template) in
the reference image will transform into one dimensional vectors. The three
similarity measures SAD, SSD, and Euclidean are used to compute the likeness
between template and all sub-windows in the reference image to find the best
match. The experimental results show the superior performance of the proposed
method over the conventional methods on various template of different sizes.
