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Author M. Visani; Oriol Ramos Terrades; Salvatore Tabbone edit  doi
openurl 
  Title A Protocol to Characterize the Descriptive Power and the Complementarity of Shape Descriptors Type Journal Article
  Year 2011 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 14 Issue 1 Pages 87-100  
  Keywords Document analysis; Shape descriptors; Symbol description; Performance characterization; Complementarity analysis  
  Abstract Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR’07, pp. 227–231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of measures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complementarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance characteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database.  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; IF 1.091 Approved no  
  Call Number Admin @ si @VRT2011 Serial 1856  
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Author Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados edit   pdf
doi  openurl
  Title CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal Type Journal Article
  Year 2012 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 15 Issue 3 Pages 243-251  
  Keywords Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths  
  Abstract 0,405JCR
The analysis of music scores has been an active research field in the last decades. However, there are no publicly available databases of handwritten music scores for the research community. In this paper we present the CVC-MUSCIMA database and ground-truth of handwritten music score images. The dataset consists of 1,000 music sheets written by 50 different musicians. It has been especially designed for writer identification and staff removal tasks. In addition to the description of the dataset, ground-truth, partitioning and evaluation metrics, we also provide some base-line results for easing the comparison between different approaches.
 
  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 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ FDG2012 Serial 2129  
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Author Partha Pratim Roy; Umapada Pal; Josep Llados edit   pdf
doi  openurl
  Title Text line extraction in graphical documents using background and foreground Type Journal Article
  Year 2012 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 15 Issue 3 Pages 227-241  
  Keywords  
  Abstract 0,405 JCR
In graphical documents (e.g., maps, engineering drawings), artistic documents etc., the text lines are annotated in multiple orientations or curvilinear way to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted. In this paper, we propose a novel method to segment such text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. In the proposed scheme, at first, individual components are detected and grouped into character clusters in a hierarchical way using size and positional information. Next, the clusters are extended in two extreme sides to determine potential candidate regions. Finally, with the help of these candidate regions,
individual lines are extracted. The experimental results are presented on different datasets of graphical documents, camera-based warped documents, noisy images containing seals, etc. The results demonstrate that our approach is robust and invariant to size and orientation of the text lines present in
the document.
 
  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 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ RPL2012b Serial 2134  
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Author David Fernandez; Josep Llados; Alicia Fornes edit  doi
openurl 
  Title A graph-based approach for segmenting touching lines in historical handwritten documents Type Journal Article
  Year 2014 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 17 Issue 3 Pages 293-312  
  Keywords Text line segmentation; Handwritten documents; Document image processing; Historical document analysis  
  Abstract Text line segmentation in handwritten documents is an important task in the recognition of historical documents. Handwritten document images contain text lines with multiple orientations, touching and overlapping characters between consecutive text lines and different document structures, making line segmentation a difficult task. In this paper, we present a new approach for handwritten text line segmentation solving the problems of touching components, curvilinear text lines and horizontally overlapping components. The proposed algorithm formulates line segmentation as finding the central path in the area between two consecutive lines. This is solved as a graph traversal problem. A graph is constructed using the skeleton of the image. Then, a path-finding algorithm is used to find the optimum path between text lines. The proposed algorithm has been evaluated on a comprehensive dataset consisting of five databases: ICDAR2009, ICDAR2013, UMD, the George Washington and the Barcelona Marriages Database. The proposed method outperforms the state-of-the-art considering the different types and difficulties of the benchmarking data.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.056; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ FLF2014 Serial 2459  
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Author Marçal Rusiñol; Volkmar Frinken; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados edit  doi
openurl 
  Title Multimodal page classification in administrative document image streams Type Journal Article
  Year 2014 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 17 Issue 4 Pages 331-341  
  Keywords Digital mail room; Multimodal page classification; Visual and textual document description  
  Abstract In this paper, we present a page classification application in a banking workflow. The proposed architecture represents administrative document images by merging visual and textual descriptions. The visual description is based on a hierarchical representation of the pixel intensity distribution. The textual description uses latent semantic analysis to represent document content as a mixture of topics. Several off-the-shelf classifiers and different strategies for combining visual and textual cues have been evaluated. A final step uses an n-gram model of the page stream allowing a finer-grained classification of pages. The proposed method has been tested in a real large-scale environment and we report results on a dataset of 70,000 pages.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; LAMP; 600.056; 600.061; 601.240; 601.223; 600.077; 600.079 Approved no  
  Call Number Admin @ si @ RFK2014 Serial 2523  
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Author Lluis Pere de las Heras; Oriol Ramos Terrades; Sergi Robles; Gemma Sanchez edit  doi
openurl 
  Title CVC-FP and SGT: a new database for structural floor plan analysis and its groundtruthing tool Type Journal Article
  Year 2015 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 18 Issue 1 Pages 15-30  
  Keywords  
  Abstract Recent results on structured learning methods have shown the impact of structural information in a wide range of pattern recognition tasks. In the field of document image analysis, there is a long experience on structural methods for the analysis and information extraction of multiple types of documents. Yet, the lack of conveniently annotated and free access databases has not benefited the progress in some areas such as technical drawing understanding. In this paper, we present a floor plan database, named CVC-FP, that is annotated for the architectural objects and their structural relations. To construct this database, we have implemented a groundtruthing tool, the SGT tool, that allows to make specific this sort of information in a natural manner. This tool has been made for general purpose groundtruthing: It allows to define own object classes and properties, multiple labeling options are possible, grants the cooperative work, and provides user and version control. We finally have collected some of the recent work on floor plan interpretation and present a quantitative benchmark for this database. Both CVC-FP database and the SGT tool are freely released to the research community to ease comparisons between methods and boost reproducible research.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.061; 600.076; 600.077 Approved no  
  Call Number Admin @ si @ HRR2015 Serial 2567  
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Author Christophe Rigaud; Clement Guerin; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier edit  doi
openurl 
  Title Knowledge-driven understanding of images in comic books Type Journal Article
  Year 2015 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 18 Issue 3 Pages 199-221  
  Keywords Document Understanding; comics analysis; expert system  
  Abstract Document analysis is an active field of research, which can attain a complete understanding of the semantics of a given document. One example of the document understanding process is enabling a computer to identify the key elements of a comic book story and arrange them according to a predefined domain knowledge. In this study, we propose a knowledge-driven system that can interact with bottom-up and top-down information to progressively understand the content of a document. We model the comic book’s and the image processing domains knowledge for information consistency analysis. In addition, different image processing methods are improved or developed to extract panels, balloons, tails, texts, comic characters and their semantic relations in an unsupervised way.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.056; 600.077 Approved no  
  Call Number RGK2015 Serial 2595  
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Author David Aldavert; Marçal Rusiñol; Ricardo Toledo; Josep Llados edit  doi
openurl 
  Title A Study of Bag-of-Visual-Words Representations for Handwritten Keyword Spotting Type Journal Article
  Year 2015 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 18 Issue 3 Pages 223-234  
  Keywords Bag-of-Visual-Words; Keyword spotting; Handwritten documents; Performance evaluation  
  Abstract 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.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; ADAS; 600.055; 600.061; 601.223; 600.077; 600.097 Approved no  
  Call Number Admin @ si @ ART2015 Serial 2679  
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Author Lluis Gomez; Dimosthenis Karatzas edit   pdf
url  openurl
  Title 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 (down) 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.
 
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  Area Expedition Conference  
  Notes DAG; 600.056; 601.197 Approved no  
  Call Number Admin @ si @ GoK2016a Serial 2862  
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Author Sounak Dey; Anguelos Nicolaou; Josep Llados; Umapada Pal edit   pdf
url  openurl
  Title Evaluation of the Effect of Improper Segmentation on Word Spotting Type Journal Article
  Year 2019 Publication International Journal on Document Analysis and Recognition Abbreviated Journal (down) IJDAR  
  Volume 22 Issue Pages 361-374  
  Keywords  
  Abstract Word spotting is an important recognition task in large-scale retrieval of document collections. In most of the cases, methods are developed and evaluated assuming perfect word segmentation. In this paper, we propose an experimental framework to quantify the goodness that word segmentation has on the performance achieved by word spotting methods in identical unbiased conditions. The framework consists of generating systematic distortions on segmentation and retrieving the original queries from the distorted dataset. We have tested our framework on several established and state-of-the-art methods using George Washington and Barcelona Marriage Datasets. The experiments done allow for an estimate of the end-to-end performance of word spotting methods.  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.097; 600.084; 600.121; 600.140; 600.129 Approved no  
  Call Number Admin @ si @ DNL2019 Serial 3455  
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