| |
Records |
Links |
|
Author |
P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes |
|
| |
Title |
A Coarse-to-Fine Word Spotting Approach for Historical Handwritten Documents Based on Graph Embedding and Graph Edit Distance |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
22nd International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
3074 - 3079 |
|
| |
Keywords |
word spotting; coarse-to-fine mechamism; graphbased representation; graph embedding; graph edit distance |
|
| |
Abstract |
Effective information retrieval on handwritten document images has always been a challenging task, especially historical ones. In the paper, we propose a coarse-to-fine handwritten word spotting approach based on graph representation. The presented model comprises both the topological and morphological signatures of the handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. Aiming at developing a practical and efficient word spotting approach for large-scale historical handwritten documents, a fast and coarse comparison is first applied to prune the regions that are not similar to the query based on the graph embedding methodology. Afterwards, the query and regions of interest are compared by graph edit distance based on the Dynamic Time Warping alignment. The proposed approach is evaluated on a public dataset containing 50 pages of historical marriage license records. The results show that the proposed approach achieves a compromise between efficiency and accuracy. |
|
| |
Address |
Stockholm; Sweden; August 2014 |
|
| |
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 |
1051-4651 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
DAG; 600.061; 602.006; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ WEG2014a |
Serial |
2515 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Alicia Fornes; Josep Llados; Joan Mas; Joana Maria Pujadas-Mora; Anna Cabre |
|
| |
Title |
A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
Digital Access to Textual Cultural Heritage Conference |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
103-108 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts. |
|
| |
Address |
Madrid; May 2014 |
|
| |
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 |
978-1-4503-2588-2 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
DATeCH |
|
| |
Notes |
DAG; 600.061; 602.006; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FLM2014 |
Serial |
2516 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
P. Wang; V. Eglin; C. Garcia; C. Largeron; Josep Llados; Alicia Fornes |
|
| |
Title |
A Novel Learning-free Word Spotting Approach Based on Graph Representation |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
11th IAPR International Workshop on Document Analysis and Systems |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
207-211 |
|
| |
Keywords |
|
|
| |
Abstract |
Effective information retrieval on handwritten document images has always been a challenging task. In this paper, we propose a novel handwritten word spotting approach based on graph representation. The presented model comprises both topological and morphological signatures of handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are established for connected components. Each word image is represented as a sequence of graphs. In order to be robust to the handwriting variations, an exhaustive merging process based on DTW alignment result is introduced in the similarity measure between word images. With respect to the computation complexity, an approximate graph edit distance approach using bipartite matching is employed for graph matching. The experiments on the George Washington dataset and the marriage records from the Barcelona Cathedral dataset demonstrate that the proposed approach outperforms the state-of-the-art structural methods. |
|
| |
Address |
Tours; France; April 2014 |
|
| |
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 |
978-1-4799-3243-6 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
DAS |
|
| |
Notes |
DAG; 600.061; 602.006; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ WEG2014b |
Serial |
2517 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Marçal Rusiñol; Volkmar Frinken; Dimosthenis Karatzas; Andrew Bagdanov; Josep Llados |
|
| |
Title |
Multimodal page classification in administrative document image streams |
Type |
Journal Article |
| |
Year |
2014 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
|
| |
Volume |
17 |
Issue |
4 |
Pages |
331-341 |
|
| |
Keywords |
Digital mail room; Multimodal page classification; Visual and textual document description |
|
| |
Abstract |
In this paper, we present a page classification application in a banking workflow. The proposed architecture represents administrative document images by merging visual and textual descriptions. The visual description is based on a hierarchical representation of the pixel intensity distribution. The textual description uses latent semantic analysis to represent document content as a mixture of topics. Several off-the-shelf classifiers and different strategies for combining visual and textual cues have been evaluated. A final step uses an n-gram model of the page stream allowing a finer-grained classification of pages. The proposed method has been tested in a real large-scale environment and we report results on a dataset of 70,000 pages. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1433-2833 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; LAMP; 600.056; 600.061; 601.240; 601.223; 600.077; 600.079 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RFK2014 |
Serial |
2523 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Francisco Cruz; Oriol Ramos Terrades |
|
| |
Title |
EM-Based Layout Analysis Method for Structured Documents |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
22nd International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
315-320 |
|
| |
Keywords |
|
|
| |
Abstract |
In this paper we present a method to perform layout analysis in structured documents. We proposed an EM-based algorithm to fit a set of Gaussian mixtures to the different regions according to the logical distribution along the page. After the convergence, we estimate the final shape of the regions according
to the parameters computed for each component of the mixture. We evaluated our method in the task of record detection in a collection of historical structured documents and performed a comparison with other previous works in this task. |
|
| |
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 |
1051-4651 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
DAG; 602.006; 600.061; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ CrR2014 |
Serial |
2530 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Francisco Alvaro; Francisco Cruz; Joan Andreu Sanchez; Oriol Ramos Terrades; Jose Miguel Benedi |
|
| |
Title |
Structure Detection and Segmentation of Documents Using 2D Stochastic Context-Free Grammars |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Neurocomputing |
Abbreviated Journal |
NEUCOM |
|
| |
Volume |
150 |
Issue |
A |
Pages |
147-154 |
|
| |
Keywords |
document image analysis; stochastic context-free grammars; text classi cation features |
|
| |
Abstract |
In this paper we de ne a bidimensional extension of Stochastic Context-Free Grammars for structure detection and segmentation of images of documents.
Two sets of text classi cation features are used to perform an initial classi cation of each zone of the page. Then, the document segmentation is obtained as the most likely hypothesis according to a stochastic grammar. We used a dataset of historical marriage license books to validate this approach. We also tested several inference algorithms for Probabilistic Graphical Models
and the results showed that the proposed grammatical model outperformed
the other methods. Furthermore, grammars also provide the document structure
along with its segmentation. |
|
| |
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; 601.158; 600.077; 600.061 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ ACS2015 |
Serial |
2531 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
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 |
|
| Permanent link to this record |
| |
|
| |
|
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 |
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 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Lluis Gomez; Dimosthenis Karatzas |
|
| |
Title |
Scene Text Recognition: No Country for Old Men? |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
1st International Workshop on Robust Reading |
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 |
IWRR |
|
| |
Notes |
DAG; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ GoK2014c |
Serial |
2538 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades |
|
| |
Title |
Spotting Symbol Using Sparsity over Learned Dictionary of Local Descriptors |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
11th IAPR International Workshop on Document Analysis and Systems |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
156-160 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper proposes a new approach to spot symbols into graphical documents using sparse representations. More specifically, a dictionary is learned from a training database of local descriptors defined over the documents. Following their sparse representations, interest points sharing similar properties are used to define interest regions. Using an original adaptation of information retrieval techniques, a vector model for interest regions and for a query symbol is built based on its sparsity in a visual vocabulary where the visual words are columns in the learned dictionary. The matching process is performed comparing the similarity between vector models. Evaluation on SESYD datasets demonstrates that our method is promising. |
|
| |
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 |
978-1-4799-3243-6 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
DAS |
|
| |
Notes |
DAG; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DTR2014 |
Serial |
2543 |
|
| Permanent link to this record |
