|
Records |
Links |
|
Author |
David Fernandez; Simone Marinai; Josep Llados; Alicia Fornes |
|
|
Title |
Contextual Word Spotting in Historical Manuscripts using Markov Logic Networks |
Type |
Conference Article |
|
Year |
2013 |
Publication |
2nd International Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
36-43 |
|
|
Keywords |
|
|
|
Abstract |
Natural languages can often be modelled by suitable grammars whose knowledge can improve the word spotting results. The implicit contextual information is even more useful when dealing with information that is intrinsically described as one collection of records. In this paper, we present one approach to word spotting which uses the contextual information of records to improve the results. The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records. The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information. |
|
|
Address |
washington; 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 |
978-1-4503-2115-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
HIP |
|
|
Notes |
DAG; 600.056; 600.045; 600.061; 602.006 |
Approved |
no |
|
|
Call Number |
Admin @ si @ FML2013 |
Serial |
2308 |
|
Permanent link to this record |
|
|
|
|
Author |
Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados |
|
|
Title |
The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition |
Type |
Journal Article |
|
Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
|
Volume |
46 |
Issue |
6 |
Pages |
1658-1669 |
|
|
Keywords |
|
|
|
Abstract |
Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Elsevier Science Inc. New York, NY, USA |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
0031-3203 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.045; 602.006; 605.203 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RFS2013 |
Serial |
2298 |
|
Permanent link to this record |
|
|
|
|
Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados; Tomokazu Sato; Masakazu Iwamura; Koichi Kise |
|
|
Title |
Key-region detection for document images -applications to administrative document retrieval |
Type |
Conference Article |
|
Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
230-234 |
|
|
Keywords |
|
|
|
Abstract |
In this paper we argue that a key-region detector designed to take into account the special characteristics of document images can result in the detection of less and more meaningful key-regions. We propose a fast key-region detector able to capture aspects of the structural information of the document, and demonstrate its efficiency by comparing against standard detectors in an administrative document retrieval scenario. We show that using the proposed detector results to a smaller number of detected key-regions and higher performance without any drop in speed compared to standard state of the art detectors. |
|
|
Address |
Washington; 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 |
1520-5363 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.056; 600.045 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GRK2013b |
Serial |
2293 |
|
Permanent link to this record |
|
|
|
|
Author |
Andreas Fischer; Ching Y. Suen; Volkmar Frinken; Kaspar Riesen; Horst Bunke |
|
|
Title |
A Fast Matching Algorithm for Graph-Based Handwriting Recognition |
Type |
Conference Article |
|
Year |
2013 |
Publication |
9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition |
Abbreviated Journal |
|
|
|
Volume |
7877 |
Issue |
|
Pages |
194-203 |
|
|
Keywords |
|
|
|
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. |
|
|
Address |
Vienna; Austria; May 2013 |
|
|
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 |
978-3-642-38220-8 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
GBR |
|
|
Notes |
DAG; 600.045; 605.203 |
Approved |
no |
|
|
Call Number |
Admin @ si @ FSF2013 |
Serial |
2294 |
|
Permanent link to this record |
|
|
|
|
Author |
Andreas Fischer; Volkmar Frinken; Horst Bunke; Ching Y. Suen |
|
|
Title |
Improving HMM-Based Keyword Spotting with Character Language Models |
Type |
Conference Article |
|
Year |
2013 |
Publication |
12th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
506-510 |
|
|
Keywords |
|
|
|
Abstract |
Facing high error rates and slow recognition speed for full text transcription of unconstrained handwriting images, keyword spotting is a promising alternative to locate specific search terms within scanned document images. We have previously proposed a learning-based method for keyword spotting using character hidden Markov models that showed a high performance when compared with traditional template image matching. In the lexicon-free approach pursued, only the text appearance was taken into account for recognition. In this paper, we integrate character n-gram language models into the spotting system in order to provide an additional language context. On the modern IAM database as well as the historical George Washington database, we demonstrate that character language models significantly improve the spotting performance. |
|
|
Address |
Washington; 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 |
1520-5363 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.045; 605.203 |
Approved |
no |
|
|
Call Number |
Admin @ si @ FFB2013 |
Serial |
2295 |
|
Permanent link to this record |
|
|
|
|
Author |
Volkmar Frinken; Andreas Fischer; Carlos David Martinez Hinarejos |
|
|
Title |
Handwriting Recognition in Historical Documents using Very Large Vocabularies |
Type |
Conference Article |
|
Year |
2013 |
Publication |
2nd International Workshop on Historical Document Imaging and Processing |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
67-72 |
|
|
Keywords |
|
|
|
Abstract |
Language models are used in automatic transcription system to resolve ambiguities. This is done by limiting the vocabulary of words that can be recognized as well as estimating the n-gram probability of the words in the given text. In the context of historical documents, a non-unified spelling and the limited amount of written text pose a substantial problem for the selection of the recognizable vocabulary as well as the computation of the word probabilities. In this paper we propose for the transcription of historical Spanish text to keep the corpus for the n-gram limited to a sample of the target text, but expand the vocabulary with words gathered from external resources. We analyze the performance of such a transcription system with different sizes of external vocabularies and demonstrate the applicability and the significant increase in recognition accuracy of using up to 300 thousand external words. |
|
|
Address |
Washington; 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 |
978-1-4503-2115-0 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
HIP |
|
|
Notes |
DAG; 600.056; 600.045; 600.061; 602.006; 602.101 |
Approved |
no |
|
|
Call Number |
Admin @ si @ FFM2013 |
Serial |
2296 |
|
Permanent link to this record |
|
|
|
|
Author |
Antonio Clavelli; Dimosthenis Karatzas; Josep Llados; Mario Ferraro; Giuseppe Boccignone |
|
|
Title |
Towards Modelling an Attention-Based Text Localization Process |
Type |
Conference Article |
|
Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
7887 |
Issue |
|
Pages |
296-303 |
|
|
Keywords |
text localization; visual attention; eye guidance |
|
|
Abstract |
This note introduces a visual attention model of text localization in real-world scenes. The core of the model built upon the proto-object concept is discussed. It is shown how such dynamic mid-level representation of the scene can be derived in the framework of an action-perception loop engaging salience, text information value computation, and eye guidance mechanisms.
Preliminary results that compare model generated scanpaths with those eye-tracked from human subjects are presented. |
|
|
Address |
Madeira; Portugal; June 2013 |
|
|
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 |
978-3-642-38627-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ CKL2013 |
Serial |
2291 |
|
Permanent link to this record |
|
|
|
|
Author |
Nuria Cirera; Alicia Fornes; Volkmar Frinken; Josep Llados |
|
|
Title |
Hybrid grammar language model for handwritten historical documents recognition |
Type |
Conference Article |
|
Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
7887 |
Issue |
|
Pages |
117-124 |
|
|
Keywords |
|
|
|
Abstract |
In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate. |
|
|
Address |
Madeira; Portugal; June 2013 |
|
|
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 |
978-3-642-38627-5 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
DAG; 602.006; 600.045; 600.061 |
Approved |
no |
|
|
Call Number |
Admin @ si @ CFF2013 |
Serial |
2292 |
|
Permanent link to this record |
|
|
|
|
Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Apostolos Antonacopoulos; Josep Llados |
|
|
Title |
An interactive appearance-based document retrieval system for historical newspapers |
Type |
Conference Article |
|
Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
84-87 |
|
|
Keywords |
|
|
|
Abstract |
In this paper we present a retrieval-based application aimed at assisting a user to semi-automatically segment an incoming flow of historical newspaper images by automatically detecting a particular type of pages based on their appearance. A visual descriptor is used to assess page similarity while a relevance feedback process allow refining the results iteratively. The application is tested on a large dataset of digitised historic newspapers. |
|
|
Address |
Barcelona; February 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 |
VISAPP |
|
|
Notes |
DAG; 600.056; 600.045; 605.203 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GRK2013a |
Serial |
2290 |
|
Permanent link to this record |
|
|
|
|
Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
|
|
Title |
Embedding of Graphs with Discrete Attributes Via Label Frequencies |
Type |
Journal Article |
|
Year |
2013 |
Publication |
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. |
|
|
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 |
Admin @ si @ GVB2013 |
Serial |
2305 |
|
Permanent link to this record |