Language Independent Word Spotting in Scanned Documents

Srihari, Sargur N.; Ball, Gregory R.

doi:10.1007/978-3-540-89533-6_14

Cited by 11 publications

(7 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A set of biologically inspired features formed by a cascade of Gabor descriptors was proposed by van der Zant and Schomaker in [57]. The combination of gradient, structural and concavity features was proposed by Srihari and Ball in [54]. All of these word representations present their strengths and weaknesses and it is hard to argue that a set of features is steadily better than another, although in the latest years a trend toward using gradient-based features can be appreciated [40].…”

Section: Introductionmentioning

confidence: 99%

A study of Bag-of-Visual-Words representations for handwritten keyword spotting

Aldavert

Rusiñol

Toledo

et al. 2015

IJDAR

View full text Add to dashboard Cite

The Bag-of-Visual-Words (BoVW) framework has gained popularity among the document image analysis community, specifically as a representation of handwritten words for recognition or spotting purposes. Although in the computer vision field the BoVW method has been greatly improved, most of the approaches in the document image analysis domain still rely on the basic implementation of the BoVW method disregarding such latest refinements. In this paper, we present a review of those improvements and its application to the keyword spotting task. We thoroughly evaluate their impact against a baseline system in the well-known George Washington dataset and compare the obtained results against nine state-of-the-art keyword spotting methods. In addition, we also compare both the baseline and improved systems with the methods presented at the Handwritten Keyword Spotting Competition 2014.

show abstract

Section: Introductionmentioning

confidence: 99%

A study of Bag-of-Visual-Words representations for handwritten keyword spotting

Aldavert

Rusiñol

Toledo

et al. 2015

IJDAR

View full text Add to dashboard Cite

show abstract

“…On manually segmented word images, the words are retrieved for a given query using the gradient based binary features described in (Zhang et al, 2004). Similar methods are also applied on English and Sanskrit documents in Srihari and Ball, 2008). In (Ball et al, 2006), in order to handle the problems of automatic word segmentation, which is especially prone to error on Arabic documents, a segmentation-free method is proposed as an alternative to the methods that require words to be segmented.…”

Section: Related Workmentioning

confidence: 99%

A line-based representation for matching words in historical manuscripts

Can¹,

Duygulu²

2011

Pattern Recognition Letters

View full text Add to dashboard Cite

Cataloged from PDF version of article.In this study, we propose a new method for retrieving and recognizing words in historical documents. We represent word images with a set of line segments. Then we provide a criterion for word matching based on matching the lines. We carry out experiments on a benchmark dataset consisting of manuscripts by George Washington, as well as on Ottoman manuscripts. (C) 2011 Elsevier B.V. All rights reserved

show abstract

“…For segmenting historical documents, generally methods that are based on the analysis and classification of the distance relationship of adjacent components are used [22,30,31,36,39,44,53,55,61]. These methods, however, are likely to fail with languages such as Ottoman, Persian, Arabic, etc., in which there are inter-word gaps as well as intraword gaps in a document, and determining which is not easy.…”

Section: Related Workmentioning

confidence: 99%

“…DTW can tolerate spatial variations unlike other methods such as XOR, Euclidean Distance Mapping, Sum of Squared Differences [47]. Alternative to the methods matching words based on whole images or profile-based features [46], recently other features are also experimented, including word contours [57], gradients [34,50,55,65], shape context descriptors [35], Harris corner detector outputs [51], line segments [12,13], and interest points [7]. In [11,21,49,57], the problem of writing style variations in multi-writer datasets is tackled, but these studies generally require isolated words.…”

Section: Related Workmentioning

confidence: 99%

Cross-document word matching for segmentation and retrieval of Ottoman divans

Duygulu

Arifoǧlu

Kalpaklı

2014

Pattern Anal Applic

View full text Add to dashboard Cite

Cataloged from PDF version of article.Motivated by the need for the automatic\ud indexing and analysis of huge number of documents in\ud Ottoman divan poetry, and for discovering new knowledge\ud to preserve and make alive this heritage, in this study we\ud propose a novel method for segmenting and retrieving\ud words in Ottoman divans. Documents in Ottoman are dif-\ud ficult to segment into words without a prior knowledge of\ud the word. In this study, using the idea that divans have\ud multiple copies (versions) by different writers in different\ud writing styles, and word segmentation in some of those\ud versions may be relatively easier to achieve than in other\ud versions, segmentation of the versions (which are difficult,\ud if not impossible, with traditional techniques) is performed\ud using information carried from the simpler version. One\ud version of a document is used as the source dataset and the\ud other version of the same document is used as the target\ud dataset. Words in the source dataset are automatically\ud extracted and used as queries to be spotted in the target\ud dataset for detecting word boundaries. We present the idea\ud of cross-document word matching for a novel task of\ud segmenting historical documents into words. We propose a\ud matching scheme based on possible combinations of\ud sequence of sub-words. We improve the performance of\ud simple features through considering the words in a context.\ud The method is applied on two versions of Layla and\ud Majnun divan by Fuzuli. The results show that, the proposed\ud word-matching-based segmentation method is\ud promising in finding the word boundaries and in retrieving\ud the words across documents

show abstract

Language Independent Word Spotting in Scanned Documents

Cited by 11 publications

References 6 publications

A study of Bag-of-Visual-Words representations for handwritten keyword spotting

A study of Bag-of-Visual-Words representations for handwritten keyword spotting

A line-based representation for matching words in historical manuscripts

Cross-document word matching for segmentation and retrieval of Ottoman divans

Contact Info

Product

Resources

About