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Author Partha Pratim Roy; Umapada Pal; Josep Llados edit  openurl
  Title Morphology Based Handwritten Line Segmentation using Foreground and Background Information Type Conference Article
  Year 2008 Publication (up) International Conference on Frontiers in Handwriting Recognition, Abbreviated Journal  
  Volume Issue Pages 241–246  
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  Address Montreal (Canada)  
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  ISSN ISBN Medium  
  Area Expedition Conference ICFHR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RPL2008a Serial 1050  
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Author Giacomo Magnifico; Beata Megyesi; Mohamed Ali Souibgui; Jialuo Chen; Alicia Fornes edit   pdf
url  openurl
  Title Lost in Transcription of Graphic Signs in Ciphers Type Conference Article
  Year 2022 Publication (up) International Conference on Historical Cryptology (HistoCrypt 2022) Abbreviated Journal  
  Volume Issue Pages 153-158  
  Keywords transcription of ciphers; hand-written text recognition of symbols; graphic signs  
  Abstract Hand-written Text Recognition techniques with the aim to automatically identify and transcribe hand-written text have been applied to historical sources including ciphers. In this paper, we compare the performance of two machine learning architectures, an unsupervised method based on clustering and a deep learning method with few-shot learning. Both models are tested on seen and unseen data from historical ciphers with different symbol sets consisting of various types of graphic signs. We compare the models and highlight their differences in performance, with their advantages and shortcomings.  
  Address Amsterdam, Netherlands, June 20-22, 2022  
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  ISSN ISBN Medium  
  Area Expedition Conference HystoCrypt  
  Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no  
  Call Number Admin @ si @ MBS2022 Serial 3731  
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Author Josep Llados; Gemma Sanchez edit  openurl
  Title Graph Matching vs. Graph Parsing in Graphics Recognition: A Combined Approach Type Journal
  Year 2004 Publication (up) International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI  
  Volume 18 Issue 3 Pages 455–473  
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  Notes DAG; IF: 0.588 Approved no  
  Call Number DAG @ dag @ LlS2004 Serial 445  
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Author Jaume Gibert; Ernest Valveny; Horst Bunke edit   pdf
doi  openurl
  Title Embedding of Graphs with Discrete Attributes Via Label Frequencies Type Journal Article
  Year 2013 Publication (up) International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI  
  Volume 27 Issue 3 Pages 1360002-1360029  
  Keywords Discrete attributed graphs; graph embedding; graph classification  
  Abstract Graph-based representations of patterns are very flexible and powerful, but they are not easily processed due to the lack of learning algorithms in the domain of graphs. Embedding a graph into a vector space solves this problem since graphs are turned into feature vectors and thus all the statistical learning machinery becomes available for graph input patterns. In this work we present a new way of embedding discrete attributed graphs into vector spaces using node and edge label frequencies. The methodology is experimentally tested on graph classification problems, using patterns of different nature, and it is shown to be competitive to state-of-the-art classification algorithms for graphs, while being computationally much more efficient.  
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  Notes DAG Approved no  
  Call Number Admin @ si @ GVB2013 Serial 2305  
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Author Josep Llados; Marçal Rusiñol; Alicia Fornes; David Fernandez; Anjan Dutta edit   pdf
doi  openurl
  Title On the Influence of Word Representations for Handwritten Word Spotting in Historical Documents Type Journal Article
  Year 2012 Publication (up) International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI  
  Volume 26 Issue 5 Pages 1263002-126027  
  Keywords Handwriting recognition; word spotting; historical documents; feature representation; shape descriptors Read More: http://www.worldscientific.com/doi/abs/10.1142/S0218001412630025  
  Abstract 0,624 JCR
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely sequence alignment using DTW as a baseline reference, a bag of visual words approach as statistical model, a pseudo-structural model based on a Loci features representation, and a structural approach where words are represented by graphs. The four approaches have been tested with two collections of historical data: the George Washington database and the marriage records from the Barcelona Cathedral. We experimentally demonstrate that statistical representations generally give a better performance, however it cannot be neglected that large descriptors are difficult to be implemented in a retrieval scenario where word spotting requires the indexation of data with million word images.
 
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  Notes DAG Approved no  
  Call Number Admin @ si @ LRF2012 Serial 2128  
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Author Ernest Valveny; Philippe Dosch edit  openurl
  Title A general framework for the evaluation of symbol recognition methods Type Journal
  Year 2006 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal  
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  Notes DAG Approved no  
  Call Number DAG @ dag @ VaD2006 Serial 686  
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Author Josep Llados; Dorothea Blostein edit  openurl
  Title Special Issue on Graphics Recognition Type Journal
  Year 2007 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 9 Issue 1 Pages 1–2  
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  Publisher Guest Editors Place of Publication Editor  
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  Notes DAG Approved no  
  Call Number DAG @ dag @ LlB2007 Serial 781  
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Author Marçal Rusiñol; Josep Llados edit  url
openurl 
  Title A Performance Evaluation Protocol for Symbol Spotting Systems in Terms of Recognition and Location Indices Type Journal Article
  Year 2009 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 12 Issue 2 Pages 83-96  
  Keywords Performance evaluation; Symbol Spotting; Graphics Recognition  
  Abstract Symbol spotting systems are intended to retrieve regions of interest from a document image database where the queried symbol is likely to be found. They shall have the ability to recognize and locate graphical symbols in a single step. In this paper, we present a set of measures to evaluate the performance of a symbol spotting system in terms of recognition abilities, location accuracy and scalability. We show that the proposed measures allow to determine the weaknesses and strengths of different methods. In particular we have tested a symbol spotting method based on a set of four different off-the-shelf shape descriptors.  
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  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RuL2009a Serial 1166  
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Author Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas edit  doi
openurl 
  Title Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model Type Journal Article
  Year 2010 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 13 Issue 3 Pages 229–241  
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  Abstract One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes.  
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  Publisher Springer-Verlag Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; IF 2009: 1,213 Approved no  
  Call Number DAG @ dag @ FLS2010a Serial 1288  
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Author Mathieu Nicolas Delalandre; Ernest Valveny; Tony Pridmore; Dimosthenis Karatzas edit  doi
openurl 
  Title Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems Type Journal Article
  Year 2010 Publication (up) International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 13 Issue 3 Pages 187-207  
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  Abstract This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results.  
  Address  
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  Publisher Springer-Verlag Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ DVP2010 Serial 1289  
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