A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Alignment by Maximization of Mutual Information
International Journal of Computer Vision
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Image registration is a fundamental task in image processing. Its aim is to match two or more pictures taken with the same or from different sensors, at different times or from different viewpoints. In image registration the use of an adequate measure of alignment is a crucial issue. Current techniques are classified in two broad categories: pixel based and feature based. All methods include some similarity measure. In this paper a new measure that combines mutual information ideas, spatial information and feature characteristics, is proposed. Edge points obtained from a Canny edge detector are used as features. Feature characteristics like location, edge strength and orientation, are taken into account to compute a joint probability distribution of corresponding edge points in two images. Mutual information based on this function is maximized to find the best alignment parameters. The approach has been tested with a collection of medical images (Nuclear Magnetic Resonance and radiotherapy portal images) and conventional video sequences, obtaining encouraging results.