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Author Nuria Cirera; Alicia Fornes; Josep Llados edit   pdf
url  doi
openurl 
  Title Hidden Markov model topology optimization for handwriting recognition Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 626-630  
  Keywords  
  Abstract In this paper we present a method to optimize the topology of linear left-to-right hidden Markov models. These models are very popular for sequential signals modeling on tasks such as handwriting recognition. Many topology definition methods select the number of states for a character model based
on character length. This can be a drawback when characters are shorter than the minimum allowed by the model, since they can not be properly trained nor recognized. The proposed method optimizes the number of states per model by automatically including convenient skip-state transitions and therefore it avoids the aforementioned problem.We discuss and compare our method with other character length-based methods such the Fixed, Bakis and Quantile methods. Our proposal performs well on off-line handwriting recognition task.
 
  Address Nancy; France; August 2015  
  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 ICDAR  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ CFL2015 Serial 2639  
Permanent link to this record
 

 
Author Juan Ignacio Toledo; Jordi Cucurull; Jordi Puiggali; Alicia Fornes; Josep Llados edit  url
doi  openurl
  Title Document Analysis Techniques for Automatic Electoral Document Processing: A Survey Type Conference Article
  Year 2015 Publication E-Voting and Identity, Proceedings of 5th international conference, VoteID 2015 Abbreviated Journal  
  Volume (down) Issue Pages 139-141  
  Keywords Document image analysis; Computer vision; Paper ballots; Paper based elections; Optical scan; Tally  
  Abstract In this paper, we will discuss the most common challenges in electoral document processing and study the different solutions from the document analysis community that can be applied in each case. We will cover Optical Mark Recognition techniques to detect voter selections in the Australian Ballot, handwritten number recognition for preferential elections and handwriting recognition for write-in areas. We will also propose some particular adjustments that can be made to those general techniques in the specific context of electoral documents.  
  Address Bern; Switzerland; September 2015  
  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 VoteID  
  Notes DAG; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ TCP2015 Serial 2641  
Permanent link to this record
 

 
Author Pau Riba; Josep Llados; Alicia Fornes edit   pdf
url  doi
openurl 
  Title Handwritten Word Spotting by Inexact Matching of Grapheme Graphs Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 781 - 785  
  Keywords  
  Abstract This paper presents a graph-based word spotting for handwritten documents. Contrary to most word spotting techniques, which use statistical representations, we propose a structural representation suitable to be robust to the inherent deformations of handwriting. Attributed graphs are constructed using a part-based approach. Graphemes extracted from shape convexities are used as stable units of handwriting, and are associated to graph nodes. Then, spatial relations between them determine graph edges. Spotting is defined in terms of an error-tolerant graph matching using bipartite-graph matching algorithm. To make the method usable in large datasets, a graph indexing approach that makes use of binary embeddings is used as preprocessing. Historical documents are used as experimental framework. The approach is comparable to statistical ones in terms of time and memory requirements, especially when dealing with large document collections.  
  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 ICDAR  
  Notes DAG; 600.077; 600.061; 602.006 Approved no  
  Call Number Admin @ si @ RLF2015b Serial 2642  
Permanent link to this record
 

 
Author J. Chazalon; Marçal Rusiñol; Jean-Marc Ogier edit  doi
openurl 
  Title Improving Document Matching Performance by Local Descriptor Filtering Type Conference Article
  Year 2015 Publication 6th IAPR International Workshop on Camera Based Document Analysis and Recognition CBDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 1216 - 1220  
  Keywords  
  Abstract In this paper we propose an effective method aimed at reducing the amount of local descriptors to be indexed in a document matching framework. In an off-line training stage, the matching between the model document and incoming images is computed retaining the local descriptors from the model that steadily produce good matches. We have evaluated this approach by using the ICDAR2015 SmartDOC dataset containing near 25 000 images from documents to be captured by a mobile device. We have tested the performance of this filtering step by using
ORB and SIFT local detectors and descriptors. The results show an important gain both in quality of the final matching as well as in time and space requirements.
 
  Address Nancy; France; August 2015  
  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 CBDAR  
  Notes DAG; 600.077; 601.223; 600.084 Approved no  
  Call Number Admin @ si @ CRO2015a Serial 2680  
Permanent link to this record
 

 
Author Jean-Christophe Burie; J. Chazalon; M. Coustaty; S. Eskenazi; Muhammad Muzzamil Luqman; M. Mehri; Nibal Nayef; Jean-Marc Ogier; S. Prum; Marçal Rusiñol edit  url
doi  openurl
  Title ICDAR2015 Competition on Smartphone Document Capture and OCR (SmartDoc) Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 1161 - 1165  
  Keywords  
  Abstract Smartphones are enabling new ways of capture,
hence arises the need for seamless and reliable acquisition and
digitization of documents, in order to convert them to editable,
searchable and a more human-readable format. Current stateof-the-art
works lack databases and baseline benchmarks for
digitizing mobile captured documents. We have organized a
competition for mobile document capture and OCR in order to
address this issue. The competition is structured into two independent
challenges: smartphone document capture, and smartphone
OCR. This report describes the datasets for both challenges
along with their ground truth, details the performance evaluation
protocols which we used, and presents the final results of the
participating methods. In total, we received 13 submissions: 8
for challenge-I, and 5 for challenge-2.
 
  Address Nancy; France; August 2015  
  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 ICDAR  
  Notes DAG; 600.077; 601.223; 600.084 Approved no  
  Call Number Admin @ si @ BCC2015 Serial 2681  
Permanent link to this record
 

 
Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados edit   pdf
doi  openurl
  Title Towards Query-by-Speech Handwritten Keyword Spotting Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 501-505  
  Keywords  
  Abstract In this paper, we present a new querying paradigm for handwritten keyword spotting. We propose to represent handwritten word images both by visual and audio representations, enabling a query-by-speech keyword spotting system. The two representations are merged together and projected to a common sub-space in the training phase. This transform allows to, given a spoken query, retrieve word instances that were only represented by the visual modality. In addition, the same method can be used backwards at no additional cost to produce a handwritten text-tospeech system. We present our first results on this new querying mechanism using synthetic voices over the George Washington
dataset.
 
  Address Nancy; France; August 2015  
  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 ICDAR  
  Notes DAG; 600.084; 600.061; 601.223; 600.077;ADAS Approved no  
  Call Number Admin @ si @ RAT2015b Serial 2682  
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Author Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados; R.Jain; D.Doermann edit  url
doi  openurl
  Title Novel Line Verification for Multiple Instance Focused Retrieval in Document Collections Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 481-485  
  Keywords  
  Abstract  
  Address Nancy; France; August 2015  
  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 ICDAR  
  Notes DAG; 600.077; 601.223; 600.084; 600.061 Approved no  
  Call Number Admin @ si @ GRK2015 Serial 2683  
Permanent link to this record
 

 
Author Marçal Rusiñol; J. Chazalon; Jean-Marc Ogier; Josep Llados edit   pdf
doi  openurl
  Title A Comparative Study of Local Detectors and Descriptors for Mobile Document Classification Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 596-600  
  Keywords  
  Abstract In this paper we conduct a comparative study of local key-point detectors and local descriptors for the specific task of mobile document classification. A classification architecture based on direct matching of local descriptors is used as baseline for the comparative study. A set of four different key-point
detectors and four different local descriptors are tested in all the possible combinations. The experiments are conducted in a database consisting of 30 model documents acquired on 6 different backgrounds, totaling more than 36.000 test images.
 
  Address Nancy; France; August 2015  
  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 ICDAR  
  Notes DAG; 600.084; 600.61; 601.223; 600.077 Approved no  
  Call Number Admin @ si @ RCO2015 Serial 2684  
Permanent link to this record
 

 
Author J. Chazalon; Marçal Rusiñol; Jean-Marc Ogier; Josep Llados edit  url
doi  openurl
  Title A Semi-Automatic Groundtruthing Tool for Mobile-Captured Document Segmentation Type Conference Article
  Year 2015 Publication 13th International Conference on Document Analysis and Recognition ICDAR2015 Abbreviated Journal  
  Volume (down) Issue Pages 621-625  
  Keywords  
  Abstract This paper presents a novel way to generate groundtruth data for the evaluation of mobile document capture systems, focusing on the first stage of the image processing pipeline involved: document object detection and segmentation in lowquality preview frames. We introduce and describe a simple, robust and fast technique based on color markers which enables a semi-automated annotation of page corners. We also detail a technique for marker removal. Methods and tools presented in the paper were successfully used to annotate, in few hours, 24889
frames in 150 video files for the smartDOC competition at ICDAR 2015
 
  Address Nancy; France; August 2015  
  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 ICDAR  
  Notes DAG; 600.084; 600.061; 601.223; 600.077 Approved no  
  Call Number Admin @ si @ CRO2015b Serial 2685  
Permanent link to this record
 

 
Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados edit  openurl
  Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Conference Article
  Year 2013 Publication 10th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume (down) Issue Pages  
  Keywords  
  Abstract  
  Address Bethlehem; PA; 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 ISBN Medium  
  Area Expedition Conference GREC  
  Notes DAG; 600.045; 600.061; 600.056 Approved no  
  Call Number Admin @ si @ HFF2013b Serial 2695  
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