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Template matching in rotated images
1Department of Computer Science, University of Kentucky, Lexington, KY 40506.
This study introduces rotationally invariant template matching using normalized invariant moments. This method simplifies matching rotated images by treating them like translated images, improving efficiency.
Area of Science:
- Computer Vision
- Image Processing
- Pattern Recognition
Background:
- Template matching is crucial for image analysis.
- Rotation poses a significant challenge in template matching.
- Existing methods often lack rotational invariance or are computationally expensive.
Purpose of the Study:
- To develop a rotationally invariant template matching technique.
- To simplify the process of matching templates in rotated images.
- To enhance the efficiency of template matching algorithms.
Main Methods:
- Utilizing normalized invariant moments within circular windows.
- Implementing a two-stage template matching approach.
- Employing zeroth-order moments for initial candidate selection.
- Using second and third-order moments for precise match localization.
Main Results:
- Achieved rotational invariance in template matching.
- Demonstrated that using normalized invariant moments in circular windows makes rotated image matching analogous to translated image matching.
- Developed a speedup technique significantly improving matching efficiency.
Conclusions:
- The proposed method effectively handles rotation in template matching.
- The two-stage approach optimizes computational performance.
- Normalized invariant moments offer a robust solution for rotationally invariant pattern recognition.
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