DocumentCode
595012
Title
Document segmentation using Relative Location Features
Author
Fernandez, F.C. ; Terrades, O.R.
Author_Institution
Comput. Vision Center, Univ. Autonoma de Barcelona, Barcelona, Spain
fYear
2012
fDate
11-15 Nov. 2012
Firstpage
1562
Lastpage
1565
Abstract
In this paper we evaluate the use of Relative Location Features (RLF) on a historical document segmentation task, and compare the quality of the results obtained on structured and unstructured documents using RLF and not using them. We prove that using these features improve the final segmentation on documents with a strong structure, while their application on unstructured documents does not show significant improvement. Although this paper is not focused on segmenting unstructured documents, results obtained on a benchmark dataset are equal or even overcome previous results of similar works.
Keywords
document image processing; feature extraction; image segmentation; RLF; document structure; historical document segmentation; relative location feature; Adaptation models; Computational modeling; Frequency domain analysis; Image segmentation; Labeling; Minimization; Training;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location
Tsukuba
ISSN
1051-4651
Print_ISBN
978-1-4673-2216-4
Type
conf
Filename
6460442
Link To Document