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Author |
Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados |
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Title |
Symbol Recognition Using a Concept Lattice of Graphical Patterns |
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Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest. |
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La Rochelle; July 2009 |
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GREC |
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DAG |
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Call Number |
DAG @ dag @ RBO2009 |
Serial |
1444 |
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Author |
Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados |
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Title |
Symbol Recognition Using a Concept Lattice of Graphical Patterns |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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Pages |
187-198 |
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Abstract |
In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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DAG |
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Admin @ si @ RBO2010 |
Serial |
2407 |
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Author |
A.Nicolaou; Andrew Bagdanov; Marcus Liwicki; Dimosthenis Karatzas |
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Title |
Sparse Radial Sampling LBP for Writer Identification |
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Conference Article |
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Year |
2015 |
Publication |
13th International Conference on Document Analysis and Recognition ICDAR2015 |
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Pages |
716-720 |
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In this paper we present the use of Sparse Radial Sampling Local Binary Patterns, a variant of Local Binary Patterns (LBP) for text-as-texture classification. By adapting and extending the standard LBP operator to the particularities of text we get a generic text-as-texture classification scheme and apply it to writer identification. In experiments on CVL and ICDAR 2013 datasets, the proposed feature-set demonstrates State-Of-the-Art (SOA) performance. Among the SOA, the proposed method is the only one that is based on dense extraction of a single local feature descriptor. This makes it fast and applicable at the earliest stages in a DIA pipeline without the need for segmentation, binarization, or extraction of multiple features. |
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Nancy; France; August 2015 |
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ICDAR |
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Notes |
DAG; 600.077 |
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no |
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Call Number |
Admin @ si @ NBL2015 |
Serial |
2692 |
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Author |
Marçal Rusiñol; Josep Llados |
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Title |
The Role of the Users in Handwritten Word Spotting Applications: Query Fusion and Relevance Feedback |
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Conference Article |
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Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
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55-60 |
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In this paper we present the importance of including the user in the loop in a handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and a baseline word spotting approach based on a bag-of-visual-words model. |
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Bari, Italy |
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978-1-4673-2262-1 |
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ICFHR |
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DAG |
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no |
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Admin @ si @ RuL2012 |
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2054 |
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Author |
Ariel Amato; Angel Sappa; Alicia Fornes; Felipe Lumbreras; Josep Llados |
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Title |
Divide and Conquer: Atomizing and Parallelizing A Task in A Mobile Crowdsourcing Platform |
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Conference Article |
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Year |
2013 |
Publication |
2nd International ACM Workshop on Crowdsourcing for Multimedia |
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21-22 |
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In this paper we present some conclusions about the advantages of having an efficient task formulation when a crowdsourcing platform is used. In particular we show how the task atomization and distribution can help to obtain results in an efficient way. Our proposal is based on a recursive splitting of the original task into a set of smaller and simpler tasks. As a result both more accurate and faster solutions are obtained. Our evaluation is performed on a set of ancient documents that need to be digitized. |
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Barcelona; October 2013 |
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978-1-4503-2396-3 |
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CrowdMM |
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ADAS; ISE; DAG; 600.054; 600.055; 600.045; 600.061; 602.006 |
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Call Number |
Admin @ si @ SLA2013 |
Serial |
2335 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
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Title |
Automatic Verification of Properly Signed Multi-page Document Images |
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Conference Article |
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Year |
2015 |
Publication |
Proceedings of the Eleventh International Symposium on Visual Computing |
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9475 |
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Pages |
327-336 |
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Keywords |
Document Image; Manual Inspection; Signature Verification; Rejection Criterion; Document Flow |
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Abstract |
In this paper we present an industrial application for the automatic screening of incoming multi-page documents in a banking workflow aimed at determining whether these documents are properly signed or not. The proposed method is divided in three main steps. First individual pages are classified in order to identify the pages that should contain a signature. In a second step, we segment within those key pages the location where the signatures should appear. The last step checks whether the signatures are present or not. Our method is tested in a real large-scale environment and we report the results when checking two different types of real multi-page contracts, having in total more than 14,500 pages. |
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Las Vegas, Nevada, USA; December 2015 |
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LNCS |
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9475 |
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ISVC |
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Notes |
DAG; 600.077 |
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Admin @ si @ |
Serial |
3189 |
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Author |
Marçal Rusiñol; T.Benkhelfallah; V. Poulain d'Andecy |
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Title |
Field Extraction from Administrative Documents by Incremental Structural Templates |
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Conference Article |
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Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
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Pages |
1100 - 1104 |
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In this paper we present an incremental framework aimed at extracting field information from administrative document images in the context of a Digital Mail-room scenario. Given a single training sample in which the user has marked which fields have to be extracted from a particular document class, a document model representing structural relationships among words is built. This model is incrementally refined as the system processes more and more documents from the same class. A reformulation of the tf-idf statistic scheme allows to adjust the importance weights of the structural relationships among words. We report in the experimental section our results obtained with a large dataset of real invoices. |
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Washington; USA; August 2013 |
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1520-5363 |
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ICDAR |
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DAG; 600.56; 600.045; 605.203; 602.101 |
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Call Number |
Admin @ si @ RBP2013 |
Serial |
2346 |
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Author |
Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados |
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Title |
Efficient segmentation-free keyword spotting in historical document collections |
Type |
Journal Article |
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Year |
2015 |
Publication |
Pattern Recognition |
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PR |
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48 |
Issue |
2 |
Pages |
545–555 |
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Historical documents; Keyword spotting; Segmentation-free; Dense SIFT features; Latent semantic analysis; Product quantization |
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Abstract |
In this paper we present an efficient segmentation-free word spotting method, applied in the context of historical document collections, that follows the query-by-example paradigm. We use a patch-based framework where local patches are described by a bag-of-visual-words model powered by SIFT descriptors. By projecting the patch descriptors to a topic space with the latent semantic analysis technique and compressing the descriptors with the product quantization method, we are able to efficiently index the document information both in terms of memory and time. The proposed method is evaluated using four different collections of historical documents achieving good performances on both handwritten and typewritten scenarios. The yielded performances outperform the recent state-of-the-art keyword spotting approaches. |
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DAG; ADAS; 600.076; 600.077; 600.061; 601.223; 602.006; 600.055 |
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Admin @ si @ RAT2015a |
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2544 |
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Author |
Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman |
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Title |
A Performance Characterization Algorithm for Symbol Localization |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
Issue |
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260–271 |
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In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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DAG |
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Admin @ si @ DRV2010 |
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2406 |
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Author |
Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman |
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Title |
A Performance Characterization Algorithm for Symbol Localization |
Type |
Conference Article |
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Year |
2009 |
Publication |
8th IAPR International Workshop on Graphics Recognition |
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3-11 |
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In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols). |
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La Rochelle; July 2009 |
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Springer |
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GREC |
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DAG |
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DAG @ dag @ DRV2009 |
Serial |
1443 |
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