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Author Pau Riba; Alicia Fornes; Josep Llados edit   pdf
url  isbn
openurl 
  Title Towards the Alignment of Handwritten Music Scores Type Book Chapter
  Year 2017 Publication International Workshop on Graphics Recognition. GREC 2015.Graphic Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 9657 Issue Pages 103-116  
  Keywords Optical Music Recognition; Handwritten Music Scores; Dynamic Time Warping alignment  
  Abstract It is very common to nd di erent versions of the same music work in archives of Opera Theaters. These di erences correspond to modi cations and annotations from the musicians. From the musicologist point of view, these variations are very interesting and deserve study.
This paper explores the alignment of music scores as a tool for automatically detecting the passages that contain such di erences. Given the diculties in the recognition of handwritten music scores, our goal is to align the music scores and at the same time, avoid the recognition of music elements as much as possible. After removing the sta lines, braces and ties, the bar lines are detected. Then, the bar units are described as a whole using the Blurred Shape Model. The bar units alignment is performed by using Dynamic Time Warping. The analysis of the alignment path is used to detect the variations in the music scores. The method has been evaluated on a subset of the CVC-MUSCIMA dataset, showing encouraging results.		  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor (down) Bart Lamiroy; R Dueire Lins  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-319-52158-9 Medium  
  Area Expedition Conference  
  Notes DAG; 600.097; 602.006; 600.121 Approved no  
  Call Number Admin @ si @ RFL2017 Serial 2955  
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Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal edit   pdf
doi  isbn
openurl 
  Title A Product Graph Based Method for Dual Subgraph Matching Applied to Symbol Spotting Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 7-11  
  Keywords Product graph; Dual edge graph; Subgraph matching; Random walks; Graph kernel  
  Abstract Product graph has been shown as a way for matching subgraphs. This paper reports the extension of the product graph methodology for subgraph matching applied to symbol spotting in graphical documents. Here we focus on the two major limitations of the previous version of the algorithm: (1) spurious nodes and edges in the graph representation and (2) inefficient node and edge attributes. To deal with noisy information of vectorized graphical documents, we consider a dual edge graph representation on the original graph representing the graphical information and the product graph is computed between the dual edge graphs of the pattern graph and the target graph. The dual edge graph with redundant edges is helpful for efficient and tolerating encoding of the structural information of the graphical documents. The adjacency matrix of the product graph locates the pair of similar edges of two operand graphs and exponentiating the adjacency matrix finds similar random walks of greater lengths. Nodes joining similar random walks between two graphs are found by combining different weighted exponentials of adjacency matrices. An experimental investigation reveals that the recall obtained by this approach is quite encouraging.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor (down) Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077 Approved no  
  Call Number Admin @ si @ DLB2014 Serial 2698  
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Author Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados edit   pdf
doi  isbn
openurl 
  Title Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 25-37  
  Keywords  
  Abstract Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor (down) Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.056; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ BDJ2014 Serial 2699  
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Author Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados edit  doi
isbn  openurl
  Title Spotting Graphical Symbols in Camera-Acquired Documents in Real Time Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 3-10  
  Keywords  
  Abstract In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor (down) Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 600.055; 600.061; 600.077 Approved no  
  Call Number Admin @ si @ RKL2014 Serial 2700  
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Author Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados edit   pdf
doi  isbn
openurl 
  Title Classification of Administrative Document Images by Logo Identification Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 49-58  
  Keywords Administrative Document Classification; Logo Recognition; Logo Spotting  
  Abstract This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier’s graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor (down) Bart Lamiroy; Jean-Marc Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.056; 600.045; 605.203; 600.077 Approved no  
  Call Number Admin @ si @ RPK2014 Serial 2701  
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Author Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta edit  doi
isbn  openurl
  Title The ICDAR/GREC 2013 Music Scores Competition: Staff Removal Type Book Chapter
  Year 2014 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 8746 Issue Pages 207-220  
  Keywords Competition; Graphics recognition; Music scores; Writer identification; Staff removal  
  Abstract The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated in both staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario concerning old and degraded music scores. For this purpose, we have generated a new set of semi-synthetic images using two degradation models that we previously introduced: local noise and 3D distortions. In this extended paper we provide an extended description of the dataset, degradation models, evaluation metrics, the participant’s methods and the obtained results that could not be presented at ICDAR and GREC proceedings due to page limitations.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor (down) B.Lamiroy; J.-M. Ogier  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-662-44853-3 Medium  
  Area Expedition Conference  
  Notes DAG; 600.077; 600.061 Approved no  
  Call Number Admin @ si @ FKV2014 Serial 2581  
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Author Hana Jarraya; Muhammad Muzzamil Luqman; Jean-Yves Ramel edit  doi
openurl 
  Title Improving Fuzzy Multilevel Graph Embedding Technique by Employing Topological Node Features: An Application to Graphics Recognition Type Book Chapter
  Year 2017 Publication Graphics Recognition. Current Trends and Challenges Abbreviated Journal  
  Volume 9657 Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor (down) B. Lamiroy; R Dueire Lins  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ JLR2017 Serial 2928  
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Author Ernest Valveny; Oriol Ramos Terrades; Joan Mas; Marçal Rusiñol edit   pdf
url  doi
isbn  openurl
  Title Interactive Document Retrieval and Classification. Type Book Chapter
  Year 2013 Publication Multimodal Interaction in Image and Video Applications Abbreviated Journal  
  Volume 48 Issue Pages 17-30  
  Keywords  
  Abstract In this chapter we describe a system for document retrieval and classification following the interactive-predictive framework. In particular, the system addresses two different scenarios of document analysis: document classification based on visual appearance and logo detection. These two classical problems of document analysis are formulated following the interactive-predictive model, taking the user interaction into account to make easier the process of annotating and labelling the documents. A system implementing this model in a real scenario is presented and analyzed. This system also takes advantage of active learning techniques to speed up the task of labelling the documents.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor (down) Angel Sappa; Jordi Vitria  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1868-4394 ISBN 978-3-642-35931-6 Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ VRM2013 Serial 2341  
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Author Jon Almazan; Lluis Gomez; Suman Ghosh; Ernest Valveny; Dimosthenis Karatzas edit  openurl
  Title WATTS: A common representation of word images and strings using embedded attributes for text recognition and retrieval Type Book Chapter
  Year 2020 Publication Visual Text Interpretation – Algorithms and Applications in Scene Understanding and Document Analysis Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor (down) Analysis”, K. Alahari; C.V. Jawahar  
  Language Summary Language Original Title  
  Series Editor Series Title Series on Advances in Computer Vision and Pattern Recognition Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.121 Approved no  
  Call Number Admin @ si @ AGG2020 Serial 3496  
Permanent link to this record
 
 
Author Mohamed Ali Souibgui edit  isbn
openurl 
  Title Document Image Enhancement and Recognition in Low Resource Scenarios: Application to Ciphers and Handwritten Text Type Book Whole
  Year 2022 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract In this thesis, we propose different contributions with the goal of enhancing and recognizing historical handwritten document images, especially the ones with rare scripts, such as cipher documents.
In the first part, some effective end-to-end models for Document Image Enhancement (DIE) using deep learning models were presented. First, Generative Adversarial Networks (cGAN) for different tasks (document clean-up, binarization, deblurring, and watermark removal) were explored. Next, we further improve the results by recovering the degraded document images into a clean and readable form by integrating a text recognizer into the cGAN model to promote the generated document image to be more readable. Afterward, we present a new encoder-decoder architecture based on vision transformers to enhance both machine-printed and handwritten document images, in an end-to-end fashion.
The second part of the thesis addresses Handwritten Text Recognition (HTR) in low resource scenarios, i.e. when only few labeled training data is available. We propose novel methods for recognizing ciphers with rare scripts. First, a few-shot object detection based method was proposed. Then, we incorporate a progressive learning strategy that automatically assignspseudo-labels to a set of unlabeled data to reduce the human labor of annotating few pages while maintaining the good performance of the model. Secondly, a data generation technique based on Bayesian Program Learning (BPL) is proposed to overcome the lack of data in such rare scripts. Thirdly, we propose a Text-Degradation Invariant Auto Encoder (Text-DIAE). This latter self-supervised model is designed to tackle two tasks, text recognition and document image enhancement. The proposed model does not exhibit limitations of previous state-of-the-art methods based on contrastive losses, while at the same time, it requires substantially fewer data samples to converge.
In the third part of the thesis, we analyze, from the user perspective, the usage of HTR systems in low resource scenarios. This contrasts with the usual research on HTR, which often focuses on technical aspects only and rarely devotes efforts on implementing software tools for scholars in Humanities.		  
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher IMPRIMA Place of Publication Editor (down) Alicia Fornes;Yousri Kessentini  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-124793-8-6 Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ Sou2022 Serial 3757  
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