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Author Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados edit   pdf
doi  openurl
  Title Embedding Document Structure to Bag-of-Words through Pair-wise Stable Key-regions Type (up) Conference Article
  Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 2903 - 2908  
  Keywords  
  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.
 
  Address Stockholm; Sweden; August 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICPR  
  Notes DAG; 600.056; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ GRK2014b Serial 2497  
Permanent link to this record
 

 
Author Joan M. Nuñez; Jorge Bernal; Miquel Ferrer; Fernando Vilariño edit   pdf
doi  openurl
  Title Impact of Keypoint Detection on Graph-based Characterization of Blood Vessels in Colonoscopy Videos Type (up) Conference Article
  Year 2014 Publication CARE workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords Colonoscopy; Graph Matching; Biometrics; Vessel; Intersection  
  Abstract We explore the potential of the use of blood vessels as anatomical landmarks for developing image registration methods in colonoscopy images. An unequivocal representation of blood vessels could be used to guide follow-up methods to track lesions over different interventions. We propose a graph-based representation to characterize network structures, such as blood vessels, based on the use of intersections and endpoints. We present a study consisting of the assessment of the minimal performance a keypoint detector should achieve so that the structure can still be recognized. Experimental results prove that, even by achieving a loss of 35% of the keypoints, the descriptive power of the associated graphs to the vessel pattern is still high enough to recognize blood vessels.  
  Address Boston; USA; September 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CARE  
  Notes MV; DAG; 600.060; 600.047; 600.077;SIAI Approved no  
  Call Number Admin @ si @ NBF2014 Serial 2504  
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Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes edit   pdf
doi  openurl
  Title A Coarse-to-Fine Word Spotting Approach for Historical Handwritten Documents Based on Graph Embedding and Graph Edit Distance Type (up) Conference Article
  Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 3074 - 3079  
  Keywords word spotting; coarse-to-fine mechamism; graphbased representation; graph embedding; graph edit distance  
  Abstract Effective information retrieval on handwritten document images has always been a challenging task, especially historical ones. In the paper, we propose a coarse-to-fine handwritten word spotting approach based on graph representation. The presented model comprises both the topological and morphological signatures of the handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. Aiming at developing a practical and efficient word spotting approach for large-scale historical handwritten documents, a fast and coarse comparison is first applied to prune the regions that are not similar to the query based on the graph embedding methodology. Afterwards, the query and regions of interest are compared by graph edit distance based on the Dynamic Time Warping alignment. The proposed approach is evaluated on a public dataset containing 50 pages of historical marriage license records. The results show that the proposed approach achieves a compromise between efficiency and accuracy.  
  Address Stockholm; Sweden; August 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1051-4651 ISBN Medium  
  Area Expedition Conference ICPR  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ WEG2014a Serial 2515  
Permanent link to this record
 

 
Author Alicia Fornes; Josep Llados; Joan Mas; Joana Maria Pujadas-Mora; Anna Cabre edit   pdf
doi  isbn
openurl 
  Title A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts Type (up) Conference Article
  Year 2014 Publication Digital Access to Textual Cultural Heritage Conference Abbreviated Journal  
  Volume Issue Pages 103-108  
  Keywords  
  Abstract In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts.  
  Address Madrid; May 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-2588-2 Medium  
  Area Expedition Conference DATeCH  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ FLM2014 Serial 2516  
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Author P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title A Novel Learning-free Word Spotting Approach Based on Graph Representation Type (up) Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 207-211  
  Keywords  
  Abstract Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods.  
  Address Tours; France; April 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ WEG2014b Serial 2517  
Permanent link to this record
 

 
Author Francisco Cruz; Oriol Ramos Terrades edit   pdf
doi  openurl
  Title EM-Based Layout Analysis Method for Structured Documents Type (up) Conference Article
  Year 2014 Publication 22nd International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 315-320  
  Keywords  
  Abstract In this paper we present a method to perform layout analysis in structured documents. We proposed an EM-based algorithm to fit a set of Gaussian mixtures to the different regions according to the logical distribution along the page. After the convergence, we estimate the final shape of the regions according
to the parameters computed for each component of the mixture. We evaluated our method in the task of record detection in a collection of historical structured documents and performed a comparison with other previous works in this task.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1051-4651 ISBN Medium  
  Area Expedition Conference ICPR  
  Notes DAG; 602.006; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ CrR2014 Serial 2530  
Permanent link to this record
 

 
Author Lluis Gomez; Dimosthenis Karatzas edit  openurl
  Title Scene Text Recognition: No Country for Old Men? Type (up) Conference Article
  Year 2014 Publication 1st International Workshop on Robust Reading Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference IWRR  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ GoK2014c Serial 2538  
Permanent link to this record
 

 
Author Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades edit  doi
isbn  openurl
  Title Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors Type (up) Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 156-160  
  Keywords  
  Abstract This paper proposes a new approach to spot symbols into graphical documents using sparse representations. More specifically, a dictionary is learned from a training database of local descriptors defined over the documents. Following their sparse representations, interest points sharing similar properties are used to define interest regions. Using an original adaptation of information retrieval techniques, a vector model for interest regions and for a query symbol is built based on its sparsity in a visual vocabulary where the visual words are columns in the learned dictionary. The matching process is performed comparing the similarity between vector models. Evaluation on SESYD datasets demonstrates that our method is promising.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ DTR2014 Serial 2543  
Permanent link to this record
 

 
Author Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier edit  doi
isbn  openurl
  Title Combining Focus Measure Operators to Predict OCR Accuracy in Mobile-Captured Document Images Type (up) Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 181 - 185  
  Keywords  
  Abstract Mobile document image acquisition is a new trend raising serious issues in business document processing workflows. Such digitization procedure is unreliable, and integrates many distortions which must be detected as soon as possible, on the mobile, to avoid paying data transmission fees, and losing information due to the inability to re-capture later a document with temporary availability. In this context, out-of-focus blur is major issue: users have no direct control over it, and it seriously degrades OCR recognition. In this paper, we concentrate on the estimation of focus quality, to ensure a sufficient legibility of a document image for OCR processing. We propose two contributions to improve OCR accuracy prediction for mobile-captured document images. First, we present 24 focus measures, never tested on document images, which are fast to compute and require no training. Second, we show that a combination of those measures enables state-of-the art performance regarding the correlation with OCR accuracy. The resulting approach is fast, robust, and easy to implement in a mobile device. Experiments are performed on a public dataset, and precise details about image processing are given.  
  Address Tours; France; April 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 601.223; 600.077 Approved no  
  Call Number Admin @ si @ RCO2014a Serial 2545  
Permanent link to this record
 

 
Author Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier edit  openurl
  Title Normalisation et validation d'images de documents capturées en mobilité Type (up) Conference Article
  Year 2014 Publication Colloque International Francophone sur l'Écrit et le Document Abbreviated Journal  
  Volume Issue Pages 109-124  
  Keywords mobile document image acquisition; perspective correction; illumination correction; quality assessment; focus measure; OCR accuracy prediction  
  Abstract Mobile document image acquisition integrates many distortions which must be corrected or detected on the device, before the document becomes unavailable or paying data transmission fees. In this paper, we propose a system to correct perspective and illumination issues, and estimate the sharpness of the image for OCR recognition. The correction step relies on fast and accurate border detection followed by illumination normalization. Its evaluation on a private dataset shows a clear improvement on OCR accuracy. The quality assessment
step relies on a combination of focus measures. Its evaluation on a public dataset shows that this simple method compares well to state of the art, learning-based methods which cannot be embedded on a mobile, and outperforms metric-based methods.
 
  Address Nancy; France; March 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CIFED  
  Notes DAG; 601.223; 600.077 Approved no  
  Call Number Admin @ si @ RCO2014b Serial 2546  
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