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Template matching with basis image reconstruction
and its image registration applications
Student
: Tzu-Hsun
Tseng
Advisor : Dr. Du-Ming Tsai
Department
of Industrial Engineering and Management
YUAN-ZE University
ABSTRACT
Template matching is a technique to find
the instance of a template in an image. Template matching techniques are
traditionally based on Image Difference and Normalized Cross Correlation.
They are very sensitive to slight changes in rotation and scale. In this
study, a basis image reconstruction method that can tolerate geometric
changes is developed for template matching. To use the basis image
reconstruction, a number of template patches with most representative
patterns are first manually or automatically selected from a reference image.
The templates then form the basis images. In the matching process, a windowed
subimage of the template size is constructed by the
linear combination of the basis images. Two measurement indicators are used
to evaluate the similarity between two compared subimages.
First, the coefficients of the linear combination of the basis images are
used as the feature vector. The Euclidean distance between the feature
vectors of the original template and the test subimage
quantifies the similarity score. The second indicator is the gray level
difference of the test subimage and its
reconstruction. Experimental results show that the basis image reconstruction
method is  in rotation and
10% in scale changes. By including templates with larger rotational angles in
the basis images, the proposed method can further identify objects with
severe direction changes.
The applications of the proposed
template matching technique in this study are industrial calibration and the
detection of moving objects (intruders) from a mobile robot. For industrial
calibration, it can be applied in positioning and calibrating a workpiece so that the assembly failure or inspection
error can be reduced. For security robots, the proposed technique can align
two consecutive images in the video sequence due to the shaking of the
camera. Then the simple image differencing can effectively and efficiently
segment the moving objects from the background. In the experiment, an image
of size 160 120 pixels needs only 0.031 seconds of processing time. The
template matching technique proposed in this study can be used for real-time
applications.
Keywords: Template matching; Basis image reconstruction; Image
registration; Security robot.
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