Intensity-Based Congealing for Unsupervised Joint Image Alignment

Markus Storer, Martin Urschler, Horst Bischof

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

We present an approach for unsupervised alignment of an ensemble of images called congealing. Our algorithm is based on image registration using the mutual information measure as a cost function. The cost function is optimized by a standard gradient descent method in a multiresolution scheme. As opposed to other congealing methods, which use the SSD measure, the mutual information measure is better suited as a similarity measure for registering images since no prior assumptions on the relation of intensities between images are required. We present alignment results on the MNIST handwritten digit database and on facial images obtained from the CVL database.
Original languageEnglish
Title of host publication20th International IEEE Conference on Pattern Recognition (ICPR)
PublisherInstitute of Electrical and Electronics Engineers
Pages1473-1476
ISBN (Print)978-1-4244-7542-1
DOIs
Publication statusPublished - 2010

Fields of Expertise

  • Information, Communication & Computing

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  • Cite this

    Storer, M., Urschler, M., & Bischof, H. (2010). Intensity-Based Congealing for Unsupervised Joint Image Alignment. In 20th International IEEE Conference on Pattern Recognition (ICPR) (pp. 1473-1476). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICPR.2010.364