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Records |
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Author |
Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera |
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Title |
Introducing the Separability Matrix for Error Correcting Output Codes Coding |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International conference on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
227-236 |
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Keywords |
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Abstract |
Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results. |
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Address |
Napoles, Italy |
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Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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LNCS |
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Edition |
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ISSN |
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ISBN |
978-3-642-21556-8 |
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Conference |
MCS |
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Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ BPB2011a |
Serial |
1771 |
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Permanent link to this record |
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Author |
Carlo Gatta; Eloi Puertas; Oriol Pujol |
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Title |
Multi-Scale Stacked Sequential Learning |
Type |
Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
44 |
Issue |
10-11 |
Pages |
2414-2416 |
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Keywords |
Stacked sequential learning; Multiscale; Multiresolution; Contextual classification |
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Abstract |
One of the most widely used assumptions in supervised learning is that data is independent and identically distributed. This assumption does not hold true in many real cases. Sequential learning is the discipline of machine learning that deals with dependent data such that neighboring examples exhibit some kind of relationship. In the literature, there are different approaches that try to capture and exploit this correlation, by means of different methodologies. In this paper we focus on meta-learning strategies and, in particular, the stacked sequential learning approach. The main contribution of this work is two-fold: first, we generalize the stacked sequential learning. This generalization reflects the key role of neighboring interactions modeling. Second, we propose an effective and efficient way of capturing and exploiting sequential correlations that takes into account long-range interactions by means of a multi-scale pyramidal decomposition of the predicted labels. Additionally, this new method subsumes the standard stacked sequential learning approach. We tested the proposed method on two different classification tasks: text lines classification in a FAQ data set and image classification. Results on these tasks clearly show that our approach outperforms the standard stacked sequential learning. Moreover, we show that the proposed method allows to control the trade-off between the detail and the desired range of the interactions. |
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Elsevier |
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LNCS |
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Notes |
MILAB;HuPBA |
Approved |
no |
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Call Number |
Admin @ si @ GPP2011 |
Serial |
1802 |
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Author |
Anjan Dutta; Josep Llados; Umapada Pal |
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Title |
Bag-of-GraphPaths Descriptors for Symbol Recognition and Spotting in Line Drawings |
Type |
Conference Article |
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Year |
2011 |
Publication |
In proceedings of 9th IAPR Workshop on Graphic Recognition |
Abbreviated Journal |
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Abstract |
Graphical symbol recognition and spotting recently have become an important research activity. In this work we present a descriptor for symbols, especially for line drawings. The descriptor is based on the graph representation of graphical objects. We construct graphs from the vectorized information of the binarized images, where the critical points detected by the vectorization algorithm are considered as nodes and the lines joining them are considered as edges. Graph paths between two nodes in a graph are the finite sequences of nodes following the order from the starting to the final node. The occurrences of different graph paths in a given graph is an important feature, as they capture the geometrical and structural attributes of a graph. So the graph representing a symbol can efficiently be represent by the occurrences of its different paths. Their occurrences in a symbol can be obtained in terms of a histogram counting the number of some fixed prototype paths, we call the histogram as the Bag-of-GraphPaths (BOGP). These BOGP histograms are used as a descriptor to measure the distance among the symbols in vector space. We use the descriptor for three applications, they are: (1) classification of the graphical symbols, (2) spotting of the architectural symbols on floorplans, (3) classification of the historical handwritten words. |
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Address |
Seoul, Korea |
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Publisher |
Springer Berlin Heidelberg |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-36823-3 |
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Expedition |
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Conference |
GREC |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ DLP2011c |
Serial |
1825 |
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Permanent link to this record |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; F. Javier Sanchez; Frederic Perez; Marius G. Linguraru; Miguel Angel Gonzalez Ballester |
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Title |
Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Workshop on Computational and Clinical Applications in Abdominal Imaging |
Abbreviated Journal |
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Volume |
7029 |
Issue |
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Pages |
223–230 |
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Keywords |
medial manifolds, abdomen. |
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Abstract |
Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations. |
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Address |
Toronto; Canada; |
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Publisher |
Springer Link |
Place of Publication |
Berlin |
Editor |
H. Yoshida et al |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-28556-1 |
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Expedition |
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Conference |
ABDI |
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Notes |
IAM;MV |
Approved |
no |
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Call Number |
IAM @ iam @ VGB2012 |
Serial |
1834 |
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Permanent link to this record |
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Author |
L.Tarazon; D. Perez; N. Serrano; V. Alabau; Oriol Ramos Terrades; A. Sanchis; A. Juan |
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Title |
Confidence Measures for Error Correction in Interactive Transcription of Handwritten Text |
Type |
Conference Article |
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Year |
2009 |
Publication |
15th International Conference on Image Analysis and Processing |
Abbreviated Journal |
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Volume |
5716 |
Issue |
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Pages |
567-574 |
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Abstract |
An effective approach to transcribe old text documents is to follow an interactive-predictive paradigm in which both, the system is guided by the human supervisor, and the supervisor is assisted by the system to complete the transcription task as efficiently as possible. In this paper, we focus on a particular system prototype called GIDOC, which can be seen as a first attempt to provide user-friendly, integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. More specifically, we focus on the handwriting recognition part of GIDOC, for which we propose the use of confidence measures to guide the human supervisor in locating possible system errors and deciding how to proceed. Empirical results are reported on two datasets showing that a word error rate not larger than a 10% can be achieved by only checking the 32% of words that are recognised with less confidence. |
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Address |
Vietri sul Mare, Italy |
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Publisher |
Springer Berlin Heidelberg |
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Series Editor |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-04145-7 |
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Conference |
ICIAP |
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Notes |
DAG |
Approved |
no |
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Call Number |
Admin @ si @ TPS2009 |
Serial |
1871 |
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Permanent link to this record |
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Author |
Miguel Angel Bautista; Oriol Pujol; Xavier Baro; Sergio Escalera |
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Title |
Introducing the Separability Matrix for Error Correcting Output Codes Coding |
Type |
Conference Article |
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Year |
2011 |
Publication |
10th International Conference on Multiple Classifier Systems |
Abbreviated Journal |
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Volume |
6713 |
Issue |
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Pages |
227-236 |
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Keywords |
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Abstract |
Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results. |
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Address |
Napoles, Italy |
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Corporate Author |
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Thesis |
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Publisher |
Springer-Verlag Berlin, Heidelberg |
Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-21556-8 |
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Expedition |
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Conference |
MCS |
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Notes |
MILAB; OR;HuPBA;MV |
Approved |
no |
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Call Number |
Admin @ si @ BPB2011b |
Serial |
1887 |
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Permanent link to this record |
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Author |
Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil |
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Title |
An illumination model of the trachea appearance in videobronchoscopy images |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Image Analysis and Recognition |
Abbreviated Journal |
LNCS |
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Volume |
7325 |
Issue |
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Pages |
313-320 |
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Keywords |
Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation |
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Abstract |
Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution. |
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Address |
Aveiro, Portugal |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31297-7 |
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Area |
800 |
Expedition |
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Conference |
ICIAR |
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Notes |
MV;IAM |
Approved |
no |
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Call Number |
IAM @ iam @ SSR2012 |
Serial |
1898 |
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Permanent link to this record |
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Author |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
Type |
Conference Article |
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Year |
2012 |
Publication |
9th International Conference on Image Analysis and Recognition |
Abbreviated Journal |
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Volume |
7324 |
Issue |
I |
Pages |
184-191 |
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Keywords |
Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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Abstract |
Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures. |
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Address |
Aveiro, Portugal |
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Corporate Author |
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Thesis |
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Publisher |
Springer-Verlag Berlin Heidelberg |
Place of Publication |
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Editor |
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Language |
english |
Summary Language |
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Original Title |
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Series Editor |
Campilho, Aurélio and Kamel, Mohamed |
Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31294-6 |
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Expedition |
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Conference |
ICIAR |
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Notes |
IAM |
Approved |
no |
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Call Number |
IAM @ iam @ MGH2012a |
Serial |
1899 |
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Permanent link to this record |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
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Title |
A Product Graph Based Method for Dual Subgraph Matching Applied to Symbol Spotting |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
Abbreviated Journal |
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Volume |
8746 |
Issue |
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Pages |
7-11 |
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Keywords |
Product graph; Dual edge graph; Subgraph matching; Random walks; Graph kernel |
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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. |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
Bart Lamiroy; Jean-Marc Ogier |
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Language |
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Summary Language |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-662-44853-3 |
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Expedition |
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Conference |
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Notes |
DAG; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ DLB2014 |
Serial |
2698 |
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Permanent link to this record |
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Author |
Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Bemedi |
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Title |
Page Segmentation of Structured Documents Using 2D Stochastic Context-Free Grammars |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
7887 |
Issue |
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Pages |
133-140 |
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Keywords |
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Abstract |
In this paper we define a bidimensional extension of Stochastic Context-Free Grammars for page segmentation of structured documents. Two sets of text classification features are used to perform an initial classification of each zone of the page. Then, the page segmentation is obtained as the most likely hypothesis according to a grammar. This approach is compared to Conditional Random Fields and results show significant improvements in several cases. Furthermore, grammars provide a detailed segmentation that allowed a semantic evaluation which also validates this model. |
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Address |
Madeira; Portugal; June 2013 |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
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Summary Language |
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Series Editor |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-38627-5 |
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Expedition |
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Conference |
IbPRIA |
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Notes |
DAG; 605.203 |
Approved |
no |
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Call Number |
Admin @ si @ ACS2013 |
Serial |
2328 |
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Permanent link to this record |
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Author |
Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny |
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Title |
Notation-invariant patch-based wall detector in architectural floor plans |
Type |
Book Chapter |
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Year |
2013 |
Publication |
Graphics Recognition. New Trends and Challenges |
Abbreviated Journal |
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Volume |
7423 |
Issue |
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Pages |
79--88 |
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Keywords |
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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. |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-36823-3 |
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Conference |
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Notes |
DAG; 600.045; 600.056; 605.203 |
Approved |
no |
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Call Number |
Admin @ si @ HMS2013 |
Serial |
2322 |
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Permanent link to this record |
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Author |
Adriana Romero; Carlo Gatta |
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Title |
Do We Really Need All These Neurons? |
Type |
Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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Volume |
7887 |
Issue |
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Pages |
460--467 |
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Keywords |
Retricted Boltzmann Machine; hidden units; unsupervised learning; classification |
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Abstract |
Restricted Boltzmann Machines (RBMs) are generative neural networks that have received much attention recently. In particular, choosing the appropriate number of hidden units is important as it might hinder their representative power. According to the literature, RBM require numerous hidden units to approximate any distribution properly. In this paper, we present an experiment to determine whether such amount of hidden units is required in a classification context. We then propose an incremental algorithm that trains RBM reusing the previously trained parameters using a trade-off measure to determine the appropriate number of hidden units. Results on the MNIST and OCR letters databases show that using a number of hidden units, which is one order of magnitude smaller than the literature estimate, suffices to achieve similar performance. Moreover, the proposed algorithm allows to estimate the required number of hidden units without the need of training many RBM from scratch. |
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Address |
Madeira; Portugal; June 2013 |
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Corporate Author |
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Thesis |
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Publisher |
Springer Berlin Heidelberg |
Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-38627-5 |
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Expedition |
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Conference |
IbPRIA |
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Notes |
MILAB; 600.046 |
Approved |
no |
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Call Number |
Admin @ si @ RoG2013 |
Serial |
2311 |
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Permanent link to this record |
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Author |
Debora Gil; Agnes Borras; Sergio Vera; Miguel Angel Gonzalez Ballester |
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Title |
A Validation Benchmark for Assessment of Medial Surface Quality for Medical Applications |
Type |
Conference Article |
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Year |
2013 |
Publication |
9th International Conference on Computer Vision Systems |
Abbreviated Journal |
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Volume |
7963 |
Issue |
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Pages |
334-343 |
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Keywords |
Medial Surfaces; Shape Representation; Medical Applications; Performance Evaluation |
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Abstract |
Confident use of medial surfaces in medical decision support systems requires evaluating their quality for detecting pathological deformations and describing anatomical volumes. Validation in the medical imaging field is a challenging task mainly due to the difficulties for getting consensual ground truth. In this paper we propose a validation benchmark for assessing medial surfaces in the context of medical applications. Our benchmark includes a home-made database of synthetic medial surfaces and volumes and specific scores for evaluating surface accuracy, its stability against volume deformations and its capabilities for accurate reconstruction of anatomical volumes. |
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Address |
Sant Petersburg; Russia; July 2013 |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-39401-0 |
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Conference |
ICVS |
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Notes |
IAM; 600.044; 600.060 |
Approved |
no |
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Call Number |
Admin @ si @ GBV2013 |
Serial |
2300 |
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Permanent link to this record |
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Author |
Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez |
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Title |
On-line lumen centre detection in gastrointestinal and respiratory endoscopy |
Type |
Conference Article |
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Year |
2013 |
Publication |
Second International Workshop Clinical Image-Based Procedures |
Abbreviated Journal |
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Volume |
8361 |
Issue |
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Pages |
31-38 |
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Keywords |
Lumen centre detection; Bronchoscopy; Colonoscopy |
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Abstract |
We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %). |
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Address |
Nagoya; Japan; September 2013 |
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Publisher |
Springer International Publishing |
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Editor |
Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus |
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LNCS |
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ISSN |
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ISBN |
978-3-319-05665-4 |
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Area |
800 |
Expedition |
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Conference |
CLIP |
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Notes |
MV; IAM; 600.047; 600.044; 600.060 |
Approved |
no |
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Call Number |
Admin @ si @ SBG2013 |
Serial |
2302 |
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Author |
Andreas Fischer; Ching Y. Suen; Volkmar Frinken; Kaspar Riesen; Horst Bunke |
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Title |
A Fast Matching Algorithm for Graph-Based Handwriting Recognition |
Type |
Conference Article |
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Year |
2013 |
Publication |
9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition |
Abbreviated Journal |
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Volume |
7877 |
Issue |
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Pages |
194-203 |
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Keywords |
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Abstract |
The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. This approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. The time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy. |
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Address |
Vienna; Austria; May 2013 |
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Publisher |
Springer Berlin Heidelberg |
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LNCS |
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Edition |
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ISSN |
0302-9743 |
ISBN |
978-3-642-38220-8 |
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Conference |
GBR |
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Notes |
DAG; 600.045; 605.203 |
Approved |
no |
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Call Number |
Admin @ si @ FSF2013 |
Serial |
2294 |
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Permanent link to this record |