Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDAR.2009.126
DC FieldValue
dc.titleAutomatic corresponding control points selection for historical document image registration
dc.contributor.authorWang, J.
dc.contributor.authorBrown, M.S.
dc.contributor.authorTan, C.L.
dc.date.accessioned2013-07-04T08:13:28Z
dc.date.available2013-07-04T08:13:28Z
dc.date.issued2009
dc.identifier.citationWang, J.,Brown, M.S.,Tan, C.L. (2009). Automatic corresponding control points selection for historical document image registration. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR : 1176-1180. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICDAR.2009.126" target="_blank">https://doi.org/10.1109/ICDAR.2009.126</a>
dc.identifier.isbn9780769537252
dc.identifier.issn15205363
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40836
dc.description.abstractImage registration is crucial for various image analysis tasks. In particular, most approaches to correction of bleed-through distortion on handwritten document images require the recto image and the verso image to be precisely registered. In this paper, we present a fully automatic method which detects specific number of corresponding control points from historical documents for the purpose of registration. First, candidate points are located by inspecting the gradient direction maps of document images. Corresponding control points are selected based on a dissimilarity metric that incorporates image intensity, gradient magnitude, gradient orientation and displacement. To improve the quality of the detected control points, median filers and consistency checking are applied to correct mismatches. Experiments on real historical document images have shown encouraging results and further improvements can be made by exploiting more sophisticated similarity metric tailored to historical documents' characteristics. © 2009 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICDAR.2009.126
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/ICDAR.2009.126
dc.description.sourcetitleProceedings of the International Conference on Document Analysis and Recognition, ICDAR
dc.description.page1176-1180
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

6
checked on Aug 14, 2022

Page view(s)

160
checked on Aug 4, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.