Image Matching by Normalized Cross-Correlation
Abstract: Correlation is widely used as an effective similarity measure in matching tasks. However, traditional correlation based matching methods are limited to the short baseline case. In this paper we propose a new correlation based method for matching two images with large camera motion. Our method is based on the rotation and scale invariant normalized cross-correlation. Both the size and the orientation of the correlation windows are determined according to the characteristic scale and the dominant direction of the interest points. Experimental results on real images demonstrate that the new method is effective for matching image pairs with significant rotation and scale changes as well as other common imaging conditions.
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