| |
Records |
Links |
|
Author |
Sounak Dey; Anguelos Nicolaou; Josep Llados; Umapada Pal |
|
| |
Title |
Local Binary Pattern for Word Spotting in Handwritten Historical Document |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
Joint IAPR International Workshops on Statistical Techniques in Pattern Recognition (SPR) and Structural and Syntactic Pattern Recognition (SSPR) |
Abbreviated Journal |
|
|
| |
Volume  |
|
Issue |
|
Pages |
574-583 |
|
| |
Keywords |
Local binary patterns; Spatial sampling; Learning-free; Word spotting; Handwritten; Historical document analysis; Large-scale data |
|
| |
Abstract |
Digital libraries store images which can be highly degraded and to index this kind of images we resort to word spotting as our information retrieval system. Information retrieval for handwritten document images is more challenging due to the difficulties in complex layout analysis, large variations of writing styles, and degradation or low quality of historical manuscripts. This paper presents a simple innovative learning-free method for word spotting from large scale historical documents combining Local Binary Pattern (LBP) and spatial sampling. This method offers three advantages: firstly, it operates in completely learning free paradigm which is very different from unsupervised learning methods, secondly, the computational time is significantly low because of the LBP features, which are very fast to compute, and thirdly, the method can be used in scenarios where annotations are not available. Finally, we compare the results of our proposed retrieval method with other methods in the literature and we obtain the best results in the learning free paradigm. |
|
| |
Address |
Merida; Mexico; December 2016 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
S+SSPR |
|
| |
Notes |
DAG; 600.097; 602.006; 603.053 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ DNL2016 |
Serial |
2876 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero |
|
| |
Title |
Banknote counterfeit detection through background texture printing analysis |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
12th IAPR Workshop on Document Analysis Systems |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This paper is focused on the detection of counterfeit photocopy banknotes. The main difficulty is to work on a real industrial scenario without any constraint about the acquisition device and with a single image. The main contributions of this paper are twofold: first the adaptation and performance evaluation of existing approaches to classify the genuine and photocopy banknotes using background texture printing analysis, which have not been applied into this context before. Second, a new dataset of Euro banknotes images acquired with several cameras under different luminance conditions to evaluate these methods. Experiments on the proposed algorithms show that mixing SIFT features and sparse coding dictionaries achieves quasi perfect classification using a linear SVM with the created dataset. Approaches using dictionaries to cover all possible texture variations have demonstrated to be robust and outperform the state-of-the-art methods using the proposed benchmark. |
|
| |
Address |
Rumania; May 2016 |
|
| |
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 |
DAS |
|
| |
Notes |
DAG; 600.061; 601.269; 600.097 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BRL2016 |
Serial |
2950 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Lluis Gomez; Y. Patel; Marçal Rusiñol; C.V. Jawahar; Dimosthenis Karatzas |
|
| |
Title |
Self‐supervised learning of visual features through embedding images into text topic spaces |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
30th IEEE Conference on Computer Vision and Pattern Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
End-to-end training from scratch of current deep architectures for new computer vision problems would require Imagenet-scale datasets, and this is not always possible. In this paper we present a method that is able to take advantage of freely available multi-modal content to train computer vision algorithms without human supervision. We put forward the idea of performing self-supervised learning of visual features by mining a large scale corpus of multi-modal (text and image) documents. We show that discriminative visual features can be learnt efficiently by training a CNN to predict the semantic context in which a particular image is more probable to appear as an illustration. For this we leverage the hidden semantic structures discovered in the text corpus with a well-known topic modeling technique. Our experiments demonstrate state of the art performance in image classification, object detection, and multi-modal retrieval compared to recent self-supervised or natural-supervised approaches. |
|
| |
Address |
Honolulu; Hawaii; July 2017 |
|
| |
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 |
CVPR |
|
| |
Notes |
DAG; 600.084; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ GPR2017 |
Serial |
2889 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Lluis Gomez |
|
| |
Title |
Exploiting Similarity Hierarchies for Multi-script Scene Text Understanding |
Type |
Book Whole |
| |
Year |
2016 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This thesis addresses the problem of automatic scene text understanding in unconstrained conditions. In particular, we tackle the tasks of multi-language and arbitrary-oriented text detection, tracking, and script identification in natural scenes.
For this we have developed a set of generic methods that build on top of the basic observation that text has always certain key visual and structural characteristics that are independent of the language or script in which it is written. Text instances in any
language or script are always formed as groups of similar atomic parts, being them either individual characters, small stroke parts, or even whole words in the case of cursive text. This holistic (sumof-parts) and recursive perspective has lead us to explore different variants of the “segmentation and grouping” paradigm of computer vision.
Scene text detection methodologies are usually based in classification of individual regions or patches, using a priory knowledge for a given script or language. Human perception of text, on the other hand, is based on perceptual organization through which
text emerges as a perceptually significant group of atomic objects.
In this thesis, we argue that the text detection problem must be posed as the detection of meaningful groups of regions. We address the problem of text detection in natural scenes from a hierarchical perspective, making explicit use of the recursive nature of text, aiming directly to the detection of region groupings corresponding to text within a hierarchy produced by an agglomerative similarity clustering process over individual regions. We propose an optimal way to construct such an hierarchy introducing a feature space designed to produce text group hypothese with high recall and a novel stopping rule combining a discriminative classifier and a probabilistic measure of group meaningfulness based in perceptual organization. Within this generic framework, we design a text-specific object proposals algorithm that, contrary to existing generic object proposals methods, aims directly to the detection of text regions groupings. For this, we abandon the rigid definition of “what is text” of traditional specialized text detectors, and move towards more fuzzy perspective of grouping-based object proposals methods.
Then, we present a hybrid algorithm for detection and tracking of scene text where the notion of region groupings plays also a central role. By leveraging the structural arrangement of text group components between consecutive frames we can improve
the overall tracking performance of the system.
Finally, since our generic detection framework is inherently designed for multi-language environments, we focus on the problem of script identification in order to build a multi-language end-toend reading system. Facing this problem with state of the art CNN classifiers is not straightforward, as they fail to address a key
characteristic of scene text instances: their extremely variable aspect ratio. Instead of resizing input images to a fixed size as in the typical use of holistic CNN classifiers, we propose a patch-based classification framework in order to preserve discriminative parts of the image that are characteristic of its class. We describe a novel method based on the use of ensembles of conjoined networks to jointly learn discriminative stroke-parts representations and their relative importance in a patch-based classification scheme. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
Ph.D. thesis |
|
| |
Publisher |
|
Place of Publication |
|
Editor |
Dimosthenis Karatzas |
|
| |
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 @ Gom2016 |
Serial |
2891 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Arnau Baro; Pau Riba; Alicia Fornes |
|
| |
Title |
Towards the recognition of compound music notes in handwritten music scores |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
15th international conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
The recognition of handwritten music scores still remains an open problem. The existing approaches can only deal with very simple handwritten scores mainly because of the variability in the handwriting style and the variability in the composition of groups of music notes (i.e. compound music notes). In this work we focus on this second problem and propose a method based on perceptual grouping for the recognition of compound music notes. Our method has been tested using several handwritten music scores of the CVC-MUSCIMA database and compared with a commercial Optical Music Recognition (OMR) software. Given that our method is learning-free, the obtained results are promising. |
|
| |
Address |
Shenzhen; China; October 2016 |
|
| |
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 |
2167-6445 |
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICFHR |
|
| |
Notes |
DAG; 600.097 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BRF2016 |
Serial |
2903 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Joana Maria Pujadas-Mora; Alicia Fornes; Josep Llados; Anna Cabre |
|
| |
Title |
Bridging the gap between historical demography and computing: tools for computer-assisted transcription and the analysis of demographic sources |
Type |
Book Chapter |
| |
Year |
2016 |
Publication |
The future of historical demography. Upside down and inside out |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
127-131 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Acco Publishers |
Place of Publication |
|
Editor |
K.Matthijs; S.Hin; H.Matsuo; J.Kok |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-94-6292-722-3 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.097 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ PFL2016 |
Serial |
2907 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Oriol Vicente; Alicia Fornes; Ramon Valdes |
|
| |
Title |
The Digital Humanities Network of the UABCie: a smart structure of research and social transference for the digital humanities |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
Digital Humanities Centres: Experiences and Perspectives |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Warsaw; Poland; December 2016 |
|
| |
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 |
DHLABS |
|
| |
Notes |
DAG; 600.097 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ VFV2016 |
Serial |
2908 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
|
| |
Title |
Using the MGGI Methodology for Category-based Language Modeling in Handwritten Marriage Licenses Books |
Type |
Conference Article |
| |
Year |
2016 |
Publication |
15th international conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
Handwritten marriage licenses books have been used for centuries by ecclesiastical and secular institutions to register marriages. The information contained in these historical documents is useful for demography studies and
genealogical research, among others. Despite the generally simple structure of the text in these documents, automatic transcription and semantic information extraction is difficult due to the distinct and evolutionary vocabulary, which is composed mainly of proper names that change along the time. In previous
works we studied the use of category-based language models to both improve the automatic transcription accuracy and make easier the extraction of semantic information. Here we analyze the main causes of the semantic errors observed in previous results and apply a Grammatical Inference technique known as MGGI to improve the semantic accuracy of the language model obtained. Using this language model, full handwritten text recognition experiments have been carried out, with results supporting the interest of the proposed approach. |
|
| |
Address |
Shenzhen; China; October 2016 |
|
| |
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 |
ICFHR |
|
| |
Notes |
DAG; 600.097; 602.006 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ RFV2016 |
Serial |
2909 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Hana Jarraya; Oriol Ramos Terrades; Josep Llados |
|
| |
Title |
Graph Embedding through Probabilistic Graphical Model applied to Symbolic Graphs |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
8th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
|
|
| |
Keywords |
Attributed Graph; Probabilistic Graphical Model; Graph Embedding; Structured Support Vector Machines |
|
| |
Abstract |
We propose a new Graph Embedding (GEM) method that takes advantages of structural pattern representation. It models an Attributed Graph (AG) as a Probabilistic Graphical Model (PGM). Then, it learns the parameters of this PGM presented by a vector. This vector is a signature of AG in a lower dimensional vectorial space. We apply Structured Support Vector Machines (SSVM) to process classification task. As first tentative, results on the GREC dataset are encouraging enough to go further on this direction. |
|
| |
Address |
Faro; Portugal; June 2017 |
|
| |
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 |
IbPRIA |
|
| |
Notes |
DAG; 600.097; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ JRL2017a |
Serial |
2953 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Lasse Martensson; Anders Hast; Alicia Fornes |
|
| |
Title |
Word Spotting as a Tool for Scribal Attribution |
Type |
Conference Article |
| |
Year |
2017 |
Publication |
2nd Conference of the association of Digital Humanities in the Nordic Countries |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
87-89 |
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
Gothenburg; Suecia; March 2017 |
|
| |
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 |
978-91-88348-83-8 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
DHN |
|
| |
Notes |
DAG; 600.097; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ MHF2017 |
Serial |
2954 |
|
| Permanent link to this record |
