Abstract: Problem statement: Template matching is a famous methodology that has a wide range of applications in image and signal processing. For a template and input image, template matching methodology finds the partial input image that is most closely matches the template image in terms of specific criterion such as the Euclidean distance or cross-correlation. Approach: In this study, a fast and robust template matching algorithm was proposed where exact Legendre moment invariants were used where a cross-correlation was employed to detect the most similar partial input image regardless of location, width and height. Results: Experimental results showed that template matching by using exact Legendre moment invariants achieve higher degree of robustness. Conclusion: Template matching by using exact Legendre moment invariants is very efficient where the high accuracy ensure the matching process and avoids any mismatching. Key words: Legendre moments, translation and scaling invariance, template matching, image features, gray-level image
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