Abstract
The paper presents an approach to multimodal image registration. The method is developed for aligning infrared (IR) and visual (RGB) images of facades. It is based on mapping clouds of points extracted by a corner detector applied to both images. The experiments show that corners are suitable features for our application. In the alignment process a number of transformation hypotheses is generated and evaluated. The evaluation is performed by measuring similarity between the RGB corners and the transformed corners from IR image. Directed partial Hausdorff distance is used as a robust similarity measure. The implemented system has been tested on various IR-RGB pairs of images of buildings. The results show that the method can be used for image registration, but also expose some typical problems. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Hrkać, T., Kalafatić, Z., & Krapac, J. (2007). Infrared-visual image registration based on corners and hausdorff distance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4522 LNCS, pp. 383–392). Springer Verlag. https://doi.org/10.1007/978-3-540-73040-8_39
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