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Author Alicia Fornes; Josep Llados; Gemma Sanchez
Title Old Handwritten Musical Symbol Classification by a Dynamic TimeWrapping Based Method Type Book Chapter
Year 2008 Publication (down) Graphics Recognition: Recent Advances and New Opportunities Abbreviated Journal
Volume 5046 Issue Pages 52–60
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 @ FLS2008a Serial 990
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Author Jose Antonio Rodriguez; Florent Perronnin
Title Local Gradient Histogram Features for Word Spotting in Unconstrained Handwritten Documents Type Book Chapter
Year 2008 Publication (down) Graphics Recognition: Recent Advances and New Opportunities Abbreviated Journal
Volume 5046 Issue Pages 188–198
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 Approved no
Call Number Admin @ si @ RoP2008a Serial 992
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Author Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados
Title Categorization of Digital Ink Elements using Spectral Features Type Book Chapter
Year 2008 Publication (down) Graphics Recognition: Recent Advances and New Opportunities Abbreviated Journal
Volume 5046 Issue Pages 188–198
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Springer–Verlag 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 @ RSL2008 Serial 1099
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Author Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone
Title On the Combination of Ridgelets Descriptors for Symbol Recognition Type Book Chapter
Year 2008 Publication (down) Graphics Recognition: Recent Advances and New Oportunities, W. Lius, J. Llados, J.M. Ogier, LNCS 5046:104–113 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
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 Approved no
Call Number DAG @ dag @ RVT2008 Serial 984
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Author Josep Llados; Gemma Sanchez; K. Tombre
Title An Error-Correction Graph Grammar to Recognize Texture Symbols. Type Miscellaneous
Year 2002 Publication (down) Graphics Recognition: Algorithms and Apllications, LNCS 2390: 128–138, Springer Verlag. Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Berlin
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 Approved no
Call Number DAG @ dag @ LST2002 Serial 281
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Author Partha Pratim Roy; Eduard Vazquez; Josep Llados; Ramon Baldrich; Umapada Pal
Title A System to Segment Text and Symbols from Color Maps Type Book Chapter
Year 2008 Publication (down) Graphics Recognition. Recent Advances and New Opportunities Abbreviated Journal
Volume 5046 Issue Pages 245-256
Keywords
Abstract
Address
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
Notes DAG;CIC Approved no
Call Number CAT @ cat @ RVL2008 Serial 1005
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Author Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny
Title Notation-invariant patch-based wall detector in architectural floor plans Type Book Chapter
Year 2013 Publication (down) Graphics Recognition. New Trends and Challenges Abbreviated Journal
Volume 7423 Issue Pages 79--88
Keywords
Abstract Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper.
Address
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 978-3-642-36823-3 Medium
Area Expedition Conference
Notes DAG; 600.045; 600.056; 605.203 Approved no
Call Number Admin @ si @ HMS2013 Serial 2322
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Author Arnau Baro; Pau Riba; Jorge Calvo-Zaragoza; Alicia Fornes
Title Optical Music Recognition by Long Short-Term Memory Networks Type Book Chapter
Year 2018 Publication (down) Graphics Recognition. Current Trends and Evolutions Abbreviated Journal
Volume 11009 Issue Pages 81-95
Keywords Optical Music Recognition; Recurrent Neural Network; Long ShortTerm Memory
Abstract Optical Music Recognition refers to the task of transcribing the image of a music score into a machine-readable format. Many music scores are written in a single staff, and therefore, they could be treated as a sequence. Therefore, this work explores the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for reading the music score sequentially, where the LSTM helps in keeping the context. For training, we have used a synthetic dataset of more than 40000 images, labeled at primitive level. The experimental results are promising, showing the benefits of our approach.
Address
Corporate Author Thesis
Publisher Springer Place of Publication Editor A. Fornes, B. Lamiroy
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN 978-3-030-02283-9 Medium
Area Expedition Conference GREC
Notes DAG; 600.097; 601.302; 601.330; 600.121 Approved no
Call Number Admin @ si @ BRC2018 Serial 3227
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Author Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal
Title A Product Graph Based Method for Dual Subgraph Matching Applied to Symbol Spotting Type Book Chapter
Year 2014 Publication (down) 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 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 Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez
Title Unsupervised and Notation-Independent Wall Segmentation in Floor Plans Using a Combination of Statistical and Structural Strategies Type Book Chapter
Year 2014 Publication (down) Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 8746 Issue Pages 109-121
Keywords Graphics recognition; Floor plan analysis; Object segmentation
Abstract In this paper we present a wall segmentation approach in floor plans that is able to work independently to the graphical notation, does not need any pre-annotated data for learning, and is able to segment multiple-shaped walls such as beams and curved-walls. This method results from the combination of the wall segmentation approaches [3, 5] presented recently by the authors. Firstly, potential straight wall segments are extracted in an unsupervised way similar to [3], but restricting even more the wall candidates considered in the original approach. Then, based on [5], these segments are used to learn the texture pattern of walls and spot the lost instances. The presented combination of both methods has been tested on 4 available datasets with different notations and compared qualitatively and quantitatively to the state-of-the-art applied on these collections. Additionally, some qualitative results on floor plans directly downloaded from the Internet are reported in the paper. The overall performance of the method demonstrates either its adaptability to different wall notations and shapes, and to document qualities and resolutions.
Address
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 978-3-662-44853-3 Medium
Area Expedition Conference
Notes DAG; ADAS; 600.076; 600.077 Approved no
Call Number Admin @ si @ HVS2014 Serial 2535
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Author Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados
Title Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans Type Book Chapter
Year 2014 Publication (down) Graphics Recognition. Current Trends and Challenges Abbreviated Journal
Volume 8746 Issue Pages 135-146
Keywords Graphics recognition; Graphics retrieval; Image classification
Abstract This paper proposes a runlength histogram signature as a perceptual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query, similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Additional retrieval results on sketched building’s facades are reported qualitatively in this paper. Its good description and its adaptability to two different sketch drawings despite its simplicity shows the interest of the proposed approach and opens a challenging research line in graphics recognition.
Address
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 978-3-662-44853-3 Medium
Area Expedition Conference
Notes DAG; ADAS; 600.045; 600.056; 600.061; 600.076; 600.077 Approved no
Call Number Admin @ si @ HFF2014 Serial 2536
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Author Alicia Fornes; V.C.Kieu; M. Visani; N.Journet; Anjan Dutta
Title The ICDAR/GREC 2013 Music Scores Competition: Staff Removal Type Book Chapter
Year 2014 Publication (down) 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 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 Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados
Title Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents Type Book Chapter
Year 2014 Publication (down) 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 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
Title Spotting Graphical Symbols in Camera-Acquired Documents in Real Time Type Book Chapter
Year 2014 Publication (down) 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 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
Title Classification of Administrative Document Images by Logo Identification Type Book Chapter
Year 2014 Publication (down) 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 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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