Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDAR.2009.86
Title: Character recognition under severe perspective distortion
Authors: Zhou, P.
Li, L. 
Tan, C.L. 
Issue Date: 2009
Source: Zhou, P.,Li, L.,Tan, C.L. (2009). Character recognition under severe perspective distortion. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR : 676-680. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDAR.2009.86
Abstract: Perspective deformation is one of the main issues needed to be addressed in real-scene character recognition. An effective recognition approach, which is able to handle severe perspective deformation, is to employ Cross Ratio Spectrum and Dynamic Time Warping techniques. However, this solution suffers from a time complexity of O(n 4). In this paper, a clustering based indexing method is proposed to index cross ratio spectra and thus expedite the recognition. Cross ratio spectra of all templates are clustered. A query is compared with the centroid of each cluster instead of spectra of all templates. Our method is 40 times faster than the previous method, and has archived about 15-time speed up while preserving almost the same recognition accuracy in the real scene character recognition experiment. © 2009 IEEE.
Source Title: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
URI: http://scholarbank.nus.edu.sg/handle/10635/41716
ISBN: 9780769537252
ISSN: 15205363
DOI: 10.1109/ICDAR.2009.86
Appears in Collections:Staff Publications

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

SCOPUSTM   
Citations

6
checked on Dec 13, 2017

Page view(s)

50
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


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