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Author Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados edit  doi
isbn  openurl
  Title (up) A Content Spotting System For Line Drawing Graphic Document Images Type Conference Article
  Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal  
  Volume 20 Issue Pages 3420–3423  
  Keywords  
  Abstract We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents.  
  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 978-1-4244-7542-1 Medium  
  Area Expedition Conference ICPR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ LBR2010b Serial 1460  
Permanent link to this record
 

 
Author Albert Gordo edit  openurl
  Title (up) A Cyclic Page Layout Descriptor for Document Classification & Retrieval Type Report
  Year 2009 Publication CVC Technical Report Abbreviated Journal  
  Volume 128 Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Computer Vision Center Thesis Master's thesis  
  Publisher Place of Publication Bellaterra, Barcelona Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes CIC;DAG Approved no  
  Call Number Admin @ si @ Gor2009 Serial 2387  
Permanent link to this record
 

 
Author Jon Almazan; Alicia Fornes; Ernest Valveny edit   pdf
doi  openurl
  Title (up) A Deformable HOG-based Shape Descriptor Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 1022-1026  
  Keywords  
  Abstract In this paper we deal with the problem of recognizing handwritten shapes. We present a new deformable feature extraction method that adapts to the shape to be described, dealing in this way with the variability introduced in the handwriting domain. It consists in a selection of the regions that best define the shape to be described, followed by the computation of histograms of oriented gradients-based features over these points. Our results significantly outperform other descriptors in the literature for the task of hand-drawn shape recognition and handwritten word retrieval  
  Address Washington; USA; August 2013  
  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 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number Admin @ si @ AFV2013 Serial 2326  
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Author Mathieu Nicolas Delalandre; Jean-Marc Ogier; Josep Llados edit  openurl
  Title (up) A Fast Cbir System of Old Ornamental Letter Type Book Chapter
  Year 2008 Publication Graphics Reognition: Recent Advances and New Opportunities Abbreviated Journal  
  Volume 5046 Issue Pages 135–144  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor W. Liu, J. Llados, J.M. Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ DOL2008 Serial 987  
Permanent link to this record
 

 
Author Lluis Gomez; Dimosthenis Karatzas edit   pdf
url  openurl
  Title (up) A fast hierarchical method for multi‐script and arbitrary oriented scene text extraction Type Journal Article
  Year 2016 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 19 Issue 4 Pages 335-349  
  Keywords scene text; segmentation; detection; hierarchical grouping; perceptual organisation  
  Abstract Typography and layout lead to the hierarchical organisation of text in words, text lines, paragraphs. This inherent structure is a key property of text in any script and language, which has nonetheless been minimally leveraged by existing text detection methods. This paper addresses the problem of text
segmentation in natural scenes from a hierarchical perspective.
Contrary to existing methods, we make explicit use of text structure, aiming directly to the detection of region groupings corresponding to text within a hierarchy produced by an agglomerative similarity clustering process over individual regions. We propose an optimal way to construct such an hierarchy introducing a feature space designed to produce text group hypotheses with
high recall and a novel stopping rule combining a discriminative classifier and a probabilistic measure of group meaningfulness based in perceptual organization. Results obtained over four standard datasets, covering text in variable orientations and different languages, demonstrate that our algorithm, while being trained in a single mixed dataset, outperforms state of the art
methods in unconstrained scenarios.
 
  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  
  Notes DAG; 600.056; 601.197 Approved no  
  Call Number Admin @ si @ GoK2016a Serial 2862  
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Author Andreas Fischer; Ching Y. Suen; Volkmar Frinken; Kaspar Riesen; Horst Bunke edit   pdf
doi  isbn
openurl 
  Title (up) A Fast Matching Algorithm for Graph-Based Handwriting Recognition Type Conference Article
  Year 2013 Publication 9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition Abbreviated Journal  
  Volume 7877 Issue Pages 194-203  
  Keywords  
  Abstract The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. This approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. The time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy.  
  Address Vienna; Austria; May 2013  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-642-38220-8 Medium  
  Area Expedition Conference GBR  
  Notes DAG; 600.045; 605.203 Approved no  
  Call Number Admin @ si @ FSF2013 Serial 2294  
Permanent link to this record
 

 
Author Mathieu Nicolas Delalandre; Jean-Marc Ogier; Josep Llados edit  openurl
  Title (up) A Fast System for the Retrieval of Ornamental Letter Image Type Conference Article
  Year 2007 Publication Seventh IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages 51–54  
  Keywords  
  Abstract  
  Address Curitiba (Brasil)  
  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 GREC  
  Notes DAG Approved no  
  Call Number DAG @ dag @ DOL2007 Serial 841  
Permanent link to this record
 

 
Author Giuseppe De Gregorio; Sanket Biswas; Mohamed Ali Souibgui; Asma Bensalah; Josep Llados; Alicia Fornes; Angelo Marcelli edit   pdf
doi  openurl
  Title (up) A Few Shot Multi-representation Approach for N-Gram Spotting in Historical Manuscripts Type Conference Article
  Year 2022 Publication Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR2022) Abbreviated Journal  
  Volume 13639 Issue Pages 3-12  
  Keywords N-gram spotting; Few-shot learning; Multimodal understanding; Historical handwritten collections  
  Abstract Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available labelled data to train the data-hungry Handwritten Text Recognition (HTR) models. The Keyword Spotting System (KWS) provides a valid alternative to HTR due to the reduction in error rate, but it is usually limited to a closed reference vocabulary. In this paper, we propose a few-shot learning paradigm for spotting sequences of a few characters (N-gram) that requires a small amount of labelled training data. We exhibit that recognition of important n-grams could reduce the system’s dependency on vocabulary. In this case, an out-of-vocabulary (OOV) word in an input handwritten line image could be a sequence of n-grams that belong to the lexicon. An extensive experimental evaluation of our proposed multi-representation approach was carried out on a subset of Bentham’s historical manuscript collections to obtain some really promising results in this direction.  
  Address December 04 – 07, 2022; Hyderabad, India  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICFHR  
  Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no  
  Call Number Admin @ si @ GBS2022 Serial 3733  
Permanent link to this record
 

 
Author Mohamed Ali Souibgui; Alicia Fornes; Y.Kessentini; C.Tudor edit   pdf
doi  openurl
  Title (up) A Few-shot Learning Approach for Historical Encoded Manuscript Recognition Type Conference Article
  Year 2021 Publication 25th International Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages 5413-5420  
  Keywords  
  Abstract Encoded (or ciphered) manuscripts are a special type of historical documents that contain encrypted text. The automatic recognition of this kind of documents is challenging because: 1) the cipher alphabet changes from one document to another, 2) there is a lack of annotated corpus for training and 3) touching symbols make the symbol segmentation difficult and complex. To overcome these difficulties, we propose a novel method for handwritten ciphers recognition based on few-shot object detection. Our method first detects all symbols of a given alphabet in a line image, and then a decoding step maps the symbol similarity scores to the final sequence of transcribed symbols. By training on synthetic data, we show that the proposed architecture is able to recognize handwritten ciphers with unseen alphabets. In addition, if few labeled pages with the same alphabet are used for fine tuning, our method surpasses existing unsupervised and supervised HTR methods for ciphers recognition.  
  Address Virtual; January 2021  
  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; 600.121; 600.140 Approved no  
  Call Number Admin @ si @ SFK2021 Serial 3449  
Permanent link to this record
 

 
Author Lluis Gomez; Dimosthenis Karatzas edit   pdf
doi  openurl
  Title (up) A fine-grained approach to scene text script identification Type Conference Article
  Year 2016 Publication 12th IAPR Workshop on Document Analysis Systems Abbreviated Journal  
  Volume Issue Pages 192-197  
  Keywords  
  Abstract This paper focuses on the problem of script identification in unconstrained scenarios. Script identification is an important prerequisite to recognition, and an indispensable condition for automatic text understanding systems designed for multi-language environments. Although widely studied for document images and handwritten documents, it remains an almost unexplored territory for scene text images. We detail a novel method for script identification in natural images that combines convolutional features and the Naive-Bayes Nearest Neighbor classifier. The proposed framework efficiently exploits the discriminative power of small stroke-parts, in a fine-grained classification framework. In addition, we propose a new public benchmark dataset for the evaluation of joint text detection and script identification in natural scenes. Experiments done in this new dataset demonstrate that the proposed method yields state of the art results, while it generalizes well to different datasets and variable number of scripts. The evidence provided shows that multi-lingual scene text recognition in the wild is a viable proposition. Source code of the proposed method is made available online.  
  Address Santorini; Grecia; April 2016  
  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 DAS  
  Notes DAG; 601.197; 600.084 Approved no  
  Call Number Admin @ si @ GoK2016b Serial 2863  
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