| |
Records |
Links |
|
Author |
Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero |
|
| |
Title  |
Evaluation of Texture Descriptors for Validation of Counterfeit Documents |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
14th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1237-1242 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper describes an exhaustive comparative analysis and evaluation of different existing texture descriptor algorithms to differentiate between genuine and counterfeit documents. We include in our experiments different categories of algorithms and compare them in different scenarios with several counterfeit datasets, comprising banknotes and identity documents. Computational time in the extraction of each descriptor is important because the final objective is to use it in a real industrial scenario. HoG and CNN based descriptors stands out statistically over the rest in terms of the F1-score/time ratio performance. |
|
| |
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 |
2379-2140 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICDAR |
|
| |
Notes |
DAG; 600.061; 601.269; 600.097; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BRL2017 |
Serial |
3092 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Salim Jouili; Salvatore Tabbone; Ernest Valveny |
|
| |
Title |
Evaluation of graph matching measures for documents retrieval |
Type |
Conference Article |
| |
Year |
2009 |
Publication |
In proceedings of 8th IAPR International Workshop on Graphics Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
13–21 |
|
| |
Keywords |
Graph Matching; Graph retrieval; structural representation; Performance Evaluation |
|
| |
Abstract |
In this paper we evaluate four graph distance measures. The analysis is performed for document retrieval tasks. For this aim, different kind of documents are used which include line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each grahp distance measure depends on the kind of data and the graph representation technique. |
|
| |
Address |
La Rochelle, France |
|
| |
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 |
0302-9743 |
ISBN |
978-3-642-13727-3 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
GREC |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
DAG @ dag @ JTV2009a |
Serial |
1230 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; Jaume Rocarias; Debora Gil |
|
| |
Title |
Evaluación automática de prácticas en Moodle para el aprendizaje autónomo en Ingenierías |
Type |
Miscellaneous |
| |
Year |
2014 |
Publication |
8th International Congress on University Teaching and Innovation |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Tarragona; juliol 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 |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
CIDUI |
|
| |
Notes |
IAM; 600.075;DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ SRM2014 |
Serial |
2458 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Youssef El Rhabi; Simon Loic; Brun Luc |
|
| |
Title |
Estimation de la pose d’une caméra à partir d’un flux vidéo en s’approchant du temps réel |
Type |
Conference Article |
| |
Year |
2015 |
Publication |
15ème édition d'ORASIS, journées francophones des jeunes chercheurs en vision par ordinateur ORASIS2015 |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
Augmented Reality; SFM; SLAM; real time pose computation; 2D/3D registration |
|
| |
Abstract |
Finding a way to estimate quickly and robustly the pose of an image is essential in augmented reality. Here we will discuss the approach we chose in order to get closer to real time by using SIFT points [4]. We propose a method based on filtering both SIFT points and images on which to focus on. Hence we will focus on relevant data. |
|
| |
Address |
Amiens; France; June 2015 |
|
| |
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 |
ORASIS |
|
| |
Notes |
DAG; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RLL2015 |
Serial |
2626 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Pau Riba; Josep Llados; Alicia Fornes |
|
| |
Title |
Error-tolerant coarse-to-fine matching model for hierarchical graphs |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
11th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
10310 |
Issue |
|
Pages |
107-117 |
|
| |
Keywords |
Graph matching; Hierarchical graph; Graph-based representation; Coarse-to-fine matching |
|
| |
Abstract |
Graph-based representations are effective tools to capture structural information from visual elements. However, retrieving a query graph from a large database of graphs implies a high computational complexity. Moreover, these representations are very sensitive to noise or small changes. In this work, a novel hierarchical graph representation is designed. Using graph clustering techniques adapted from graph-based social media analysis, we propose to generate a hierarchy able to deal with different levels of abstraction while keeping information about the topology. For the proposed representations, a coarse-to-fine matching method is defined. These approaches are validated using real scenarios such as classification of colour images and handwritten word spotting. |
|
| |
Address |
Anacapri; Italy; May 2017 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
Pasquale Foggia; Cheng-Lin Liu; Mario Vento |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
GbRPR |
|
| |
Notes |
DAG; 600.097; 601.302; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RLF2017a |
Serial |
2951 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Ricardo Toledo; Ramon Baldrich; Ernest Valveny; Petia Radeva |
|
| |
Title |
Enhancing snakes for vessel detection in angiography images. |
Type |
Miscellaneous |
| |
Year |
2002 |
Publication |
Proceedings of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002: 139–144. |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
MILAB;DAG;CIC;ADAS |
Approved |
no |
|
| |
Call Number |
BCNPCL @ bcnpcl @ TBV2002 |
Serial |
300 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
S.K. Jemni; Mohamed Ali Souibgui; Yousri Kessentini; Alicia Fornes |
|
| |
Title |
Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement |
Type |
Journal Article |
| |
Year |
2022 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
| |
Volume |
123 |
Issue |
|
Pages |
108370 |
|
| |
Keywords |
|
|
| |
Abstract |
Handwritten document images can be highly affected by degradation for different reasons: Paper ageing, daily-life scenarios (wrinkles, dust, etc.), bad scanning process and so on. These artifacts raise many readability issues for current Handwritten Text Recognition (HTR) algorithms and severely devalue their efficiency. In this paper, we propose an end to end architecture based on Generative Adversarial Networks (GANs) to recover the degraded documents into a and form. Unlike the most well-known document binarization methods, which try to improve the visual quality of the degraded document, the proposed architecture integrates a handwritten text recognizer that promotes the generated document image to be more readable. To the best of our knowledge, this is the first work to use the text information while binarizing handwritten documents. Extensive experiments conducted on degraded Arabic and Latin handwritten documents demonstrate the usefulness of integrating the recognizer within the GAN architecture, which improves both the visual quality and the readability of the degraded document images. Moreover, we outperform the state of the art in H-DIBCO challenges, after fine tuning our pre-trained model with synthetically degraded Latin handwritten images, on 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 |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.124; 600.121; 602.230 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ JSK2022 |
Serial |
3613 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Manuel Carbonell; Joan Mas; Mauricio Villegas; Alicia Fornes; Josep Llados |
|
| |
Title |
End-to-End Handwritten Text Detection and Transcription in Full Pages |
Type |
Conference Article |
| |
Year |
2019 |
Publication |
2nd International Workshop on Machine Learning |
Abbreviated Journal |
|
|
| |
Volume |
5 |
Issue |
|
Pages |
29-34 |
|
| |
Keywords |
Handwritten Text Recognition; Layout Analysis; Text segmentation; Deep Neural Networks; Multi-task learning |
|
| |
Abstract |
When transcribing handwritten document images, inaccuracies in the text segmentation step often cause errors in the subsequent transcription step. For this reason, some recent methods propose to perform the recognition at paragraph level. But still, errors in the segmentation of paragraphs can affect
the transcription performance. In this work, we propose an end-to-end framework to transcribe full pages. The joint text detection and transcription allows to remove the layout analysis requirement at test time. The experimental results show that our approach can achieve comparable results to models that assume
segmented paragraphs, and suggest that joining the two tasks brings an improvement over doing the two tasks separately. |
|
| |
Address |
Sydney; Australia; September 2019 |
|
| |
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 |
ICDAR WML |
|
| |
Notes |
DAG; 600.140; 601.311; 600.140 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ CMV2019 |
Serial |
3353 |
|
| 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 |
| |
|
| |
|
Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
|
| |
Title |
Embedding Document Structure to Bag-of-Words through Pair-wise Stable Key-regions |
Type |
Conference Article |
| |
Year |
2014 |
Publication |
22nd International Conference on Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
2903 - 2908 |
|
| |
Keywords |
|
|
| |
Abstract |
Since the document structure carries valuable discriminative information, plenty of efforts have been made for extracting and understanding document structure among which layout analysis approaches are the most commonly used. In this paper, Distance Transform based MSER (DTMSER) is employed to efficiently extract the document structure as a dendrogram of key-regions which roughly correspond to structural elements such as characters, words and paragraphs. Inspired by the Bag
of Words (BoW) framework, we propose an efficient method for structural document matching by representing the document image as a histogram of key-region pairs encoding structural relationships.
Applied to the scenario of document image retrieval, experimental results demonstrate a remarkable improvement when comparing the proposed method with typical BoW and pyramidal BoW methods. |
|
| |
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 |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICPR |
|
| |
Notes |
DAG; 600.056; 600.061; 600.077 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ GRK2014b |
Serial |
2497 |
|
| Permanent link to this record |
