A Fast and Accurate Image-Registration Algorithm Using Prior Knowledge

We propose an iterative image-registration algorithm to estimate the homography between two plane surfaces based on prior information. The difference to established methods using algorithms like SIFT and SURF lies in the kind of features used for the calculation. Instead of patch-based features, the...

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Published in2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA) pp. 1 - 8
Main Authors Kallwies, Jan, Engler, Torsten, Wuensche, Hans-Joachim
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2016
Subjects
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DOI10.1109/DICTA.2016.7796988

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Abstract We propose an iterative image-registration algorithm to estimate the homography between two plane surfaces based on prior information. The difference to established methods using algorithms like SIFT and SURF lies in the kind of features used for the calculation. Instead of patch-based features, the algorithm uses prior information to search for features along 1-D signals and their expected counterparts. This reduces the computational complexity by one dimension and decreases the search space for feature correspondences enormously. The reduction in dimension and the comparison of whole image strips yields better accuracy and lower computational effort, while being able to handle any perspective transformation. Based on a broad variety of test images, an estimation of sufficient prior knowledge and a comparison with the established methods SIFT, SURF and ORB is given. We show that the iterative nature and the strip-based approach makes the algorithm very flexible, thereby achieving high accuracy at low computational effort.
AbstractList We propose an iterative image-registration algorithm to estimate the homography between two plane surfaces based on prior information. The difference to established methods using algorithms like SIFT and SURF lies in the kind of features used for the calculation. Instead of patch-based features, the algorithm uses prior information to search for features along 1-D signals and their expected counterparts. This reduces the computational complexity by one dimension and decreases the search space for feature correspondences enormously. The reduction in dimension and the comparison of whole image strips yields better accuracy and lower computational effort, while being able to handle any perspective transformation. Based on a broad variety of test images, an estimation of sufficient prior knowledge and a comparison with the established methods SIFT, SURF and ORB is given. We show that the iterative nature and the strip-based approach makes the algorithm very flexible, thereby achieving high accuracy at low computational effort.
Author Wuensche, Hans-Joachim
Engler, Torsten
Kallwies, Jan
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  organization: Dept. of Aerosp. Eng., Univ. of the Bundeswehr, Munich, Germany
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Snippet We propose an iterative image-registration algorithm to estimate the homography between two plane surfaces based on prior information. The difference to...
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SubjectTerms Accuracy
Cameras
Estimation
Feature extraction
Image reconstruction
Image registration
Iterative algorithms
Real-time systems
Strips
Transforms
Title A Fast and Accurate Image-Registration Algorithm Using Prior Knowledge
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