DocumentCode
178389
Title
Embedding Document Structure to Bag-of-Words through Pair-wise Stable Key-Regions
Author
Hongxing Gao ; Rusinol, M. ; Karatzas, D. ; Llados, J.
Author_Institution
Dept. Cienc. de la Computacio, Univ. Autonoma de Barcelona, Bellaterra, Spain
fYear
2014
fDate
24-28 Aug. 2014
Firstpage
2903
Lastpage
2908
Abstract
Since the document structure carries valuable discriminative information, plenty of efforts have been made for extracting and understanding document structure among which layout analysis approaches are the most commonly used. In this paper, Distance Transform based MSER (DTMSER) is employed to efficiently extract the document structure as a dendrogram of key-regions which roughly correspond to structural elements such as characters, words and paragraphs. Inspired by the Bag of Words (BoW) framework, we propose an efficient method for structural document matching by representing the document image as a histogram of key-region pairs encoding structural relationships. Applied to the scenario of document image retrieval, experimental results demonstrate a remarkable improvement when comparing the proposed method with typical BoW and pyramidal BoW methods.
Keywords
document image processing; image matching; image retrieval; DTMSER; bag of words framework; characters; dendrogram; distance transform based MSER; document image retrieval; embedding document structure; histogram; layout analysis approaches; pairwise stable key-regions; paragraphs; pyramidal BoW methods; structural document matching; structural elements; typical BoW methods; words; Algorithm design and analysis; Feature extraction; Histograms; Indexing; Layout; Transforms; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location
Stockholm
ISSN
1051-4651
Type
conf
DOI
10.1109/ICPR.2014.500
Filename
6977213
Link To Document