| |
Records |
Links |
|
Author |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait (eds) |
|
| |
Title |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition. 18th International Conference, ICFHR 2022 |
Type |
Book Whole |
| |
Year |
2022 |
Publication  |
Frontiers in Handwriting Recognition. |
Abbreviated Journal |
|
|
| |
Volume |
13639 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
|
|
| |
Address |
ICFHR 2022, Hyderabad, India, December 4–7, 2022 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer |
Place of Publication |
|
Editor |
Utkarsh Porwal; Alicia Fornes; Faisal Shafait |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-031-21648-0 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
ICFHR |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ PFS2022 |
Serial |
3809 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Giuseppe De Gregorio; Sanket Biswas; Mohamed Ali Souibgui; Asma Bensalah; Josep Llados; Alicia Fornes; Angelo Marcelli |
|
| |
Title |
A Few Shot Multi-representation Approach for N-Gram Spotting in Historical Manuscripts |
Type |
Conference Article |
| |
Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR2022) |
Abbreviated Journal |
|
|
| |
Volume |
13639 |
Issue |
|
Pages |
3-12 |
|
| |
Keywords |
N-gram spotting; Few-shot learning; Multimodal understanding; Historical handwritten collections |
|
| |
Abstract |
Despite recent advances in automatic text recognition, the performance remains moderate when it comes to historical manuscripts. This is mainly because of the scarcity of available labelled data to train the data-hungry Handwritten Text Recognition (HTR) models. The Keyword Spotting System (KWS) provides a valid alternative to HTR due to the reduction in error rate, but it is usually limited to a closed reference vocabulary. In this paper, we propose a few-shot learning paradigm for spotting sequences of a few characters (N-gram) that requires a small amount of labelled training data. We exhibit that recognition of important n-grams could reduce the system’s dependency on vocabulary. In this case, an out-of-vocabulary (OOV) word in an input handwritten line image could be a sequence of n-grams that belong to the lexicon. An extensive experimental evaluation of our proposed multi-representation approach was carried out on a subset of Bentham’s historical manuscript collections to obtain some really promising results in this direction. |
|
| |
Address |
December 04 – 07, 2022; Hyderabad, India |
|
| |
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 |
ICFHR |
|
| |
Notes |
DAG; 600.121; 600.162; 602.230; 600.140 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ GBS2022 |
Serial |
3733 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Arnau Baro; Pau Riba; Alicia Fornes |
|
| |
Title |
Musigraph: Optical Music Recognition Through Object Detection and Graph Neural Network |
Type |
Conference Article |
| |
Year |
2022 |
Publication |
Frontiers in Handwriting Recognition. International Conference on Frontiers in Handwriting Recognition (ICFHR2022) |
Abbreviated Journal |
|
|
| |
Volume |
13639 |
Issue |
|
Pages |
171-184 |
|
| |
Keywords |
Object detection; Optical music recognition; Graph neural network |
|
| |
Abstract |
During the last decades, the performance of optical music recognition has been increasingly improving. However, and despite the 2-dimensional nature of music notation (e.g. notes have rhythm and pitch), most works treat musical scores as a sequence of symbols in one dimension, which make their recognition still a challenge. Thus, in this work we explore the use of graph neural networks for musical score recognition. First, because graphs are suited for n-dimensional representations, and second, because the combination of graphs with deep learning has shown a great performance in similar applications. Our methodology consists of: First, we will detect each isolated/atomic symbols (those that can not be decomposed in more graphical primitives) and the primitives that form a musical symbol. Then, we will build the graph taking as root node the notehead and as leaves those primitives or symbols that modify the note’s rhythm (stem, beam, flag) or pitch (flat, sharp, natural). Finally, the graph is translated into a human-readable character sequence for a final transcription and evaluation. Our method has been tested on more than five thousand measures, showing promising results. |
|
| |
Address |
December 04 – 07, 2022; Hyderabad, India |
|
| |
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 |
ICFHR |
|
| |
Notes |
DAG; 600.162; 600.140; 602.230 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ BRF2022b |
Serial |
3740 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados |
|
| |
Title |
Multilevel Analysis of Attributed Graphs for Explicit Graph Embedding in Vector Spaces |
Type |
Book Chapter |
| |
Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
1-26 |
|
| |
Keywords |
|
|
| |
Abstract |
Ability to recognize patterns is among the most crucial capabilities of human beings for their survival, which enables them to employ their sophisticated neural and cognitive systems [1], for processing complex audio, visual, smell, touch, and taste signals. Man is the most complex and the best existing system of pattern recognition. Without any explicit thinking, we continuously compare, classify, and identify huge amount of signal data everyday [2], starting from the time we get up in the morning till the last second we fall asleep. This includes recognizing the face of a friend in a crowd, a spoken word embedded in noise, the proper key to lock the door, smell of coffee, the voice of a favorite singer, the recognition of alphabetic characters, and millions of more tasks that we perform on regular basis. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer New York |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-1-4614-4456-5 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ LRL2013b |
Serial |
2271 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Miquel Ferrer; I. Bardaji; Ernest Valveny; Dimosthenis Karatzas; Horst Bunke |
|
| |
Title |
Median Graph Computation by Means of Graph Embedding into Vector Spaces |
Type |
Book Chapter |
| |
Year |
2013 |
Publication |
Graph Embedding for Pattern Analysis |
Abbreviated Journal |
|
|
| |
Volume |
|
Issue |
|
Pages |
45-72 |
|
| |
Keywords |
|
|
| |
Abstract |
In pattern recognition [8, 14], a key issue to be addressed when designing a system is how to represent input patterns. Feature vectors is a common option. That is, a set of numerical features describing relevant properties of the pattern are computed and arranged in a vector form. The main advantages of this kind of representation are computational simplicity and a well sound mathematical foundation. Thus, a large number of operations are available to work with vectors and a large repository of algorithms for pattern analysis and classification exist. However, the simple structure of feature vectors might not be the best option for complex patterns where nonnumerical features or relations between different parts of the pattern become relevant. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer New York |
Place of Publication |
|
Editor |
Yun Fu; Yungian Ma |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-1-4614-4456-5 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FBV2013 |
Serial |
2421 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
|
| |
Title |
Symbol recognition: current advances and perspectives |
Type |
Book Chapter |
| |
Year |
2002 |
Publication |
Graphics Recognition Algorithms And Applications |
Abbreviated Journal |
LNCS |
|
| |
Volume |
2390 |
Issue |
|
Pages |
104-128 |
|
| |
Keywords |
|
|
| |
Abstract |
The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content. |
|
| |
Address |
London, UK |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer-Verlag |
Place of Publication |
|
Editor |
Dorothea Blostein and Young- Bin Kwon |
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
Lecture Notes in Computer Science |
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
3-540-44066-6 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
GREC |
|
| |
Notes |
DAG; IAM; |
Approved |
no |
|
| |
Call Number |
IAM @ iam @ LVS2002 |
Serial |
1572 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Josep Llados; Gemma Sanchez; Enric Marti |
|
| |
Title |
A string based method to recognize symbols and structural textures in architectural plans |
Type |
Book Chapter |
| |
Year |
1998 |
Publication |
Graphics Recognition Algorithms and Systems Second International Workshop, GREC' 97 Nancy, France, August 22–23, 1997 Selected Papers |
Abbreviated Journal |
LNCS |
|
| |
Volume |
1389 |
Issue |
1998 |
Pages |
91-103 |
|
| |
Keywords |
|
|
| |
Abstract |
This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer Link |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
LNCS |
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
|
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; IAM |
Approved |
no |
|
| |
Call Number |
IAM @ iam @ SLE1998 |
Serial |
1573 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Ernest Valveny; Enric Marti |
|
| |
Title |
Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition |
Type |
Journal Article |
| |
Year |
2000 |
Publication |
Graphics Recognition Recent Advances |
Abbreviated Journal |
|
|
| |
Volume |
1941 |
Issue |
|
Pages |
193-208 |
|
| |
Keywords |
|
|
| |
Abstract |
We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols. |
|
| |
Address |
|
|
| |
Corporate Author |
Springer Verlag |
Thesis |
|
|
| |
Publisher |
Springer Verlag |
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;IAM; |
Approved |
no |
|
| |
Call Number |
IAM @ iam @ MVA2000 |
Serial |
1655 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Alicia Fornes; Bart Lamiroy |
|
| |
Title |
Graphics Recognition, Current Trends and Evolutions |
Type |
Book Whole |
| |
Year |
2018 |
Publication |
Graphics Recognition, Current Trends and Evolutions |
Abbreviated Journal |
|
|
| |
Volume |
11009 |
Issue |
|
Pages |
|
|
| |
Keywords |
|
|
| |
Abstract |
This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
Springer International Publishing |
Place of Publication |
|
Editor |
|
|
| |
Language |
|
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
|
ISBN |
978-3-030-02283-9 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
DAG; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ FoL2018 |
Serial |
3171 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Salim Jouili; Salvatore Tabbone; Ernest Valveny |
|
| |
Title |
Comparing Graph Similarity Measures for Graphical Recognition |
Type |
Book Chapter |
| |
Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
Abbreviated Journal |
|
|
| |
Volume |
6020 |
Issue |
|
Pages |
37-48 |
|
| |
Keywords |
|
|
| |
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 including line drawings (symbols), ancient documents (ornamental letters), shapes and trademark-logos. The experimental results show that the performance of each graph distance measure depends on the kind of data and the graph representation technique. |
|
| |
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 |
978-3-642-13727-3 |
Medium |
|
|
| |
Area |
|
Expedition |
|
Conference |
GREC |
|
| |
Notes |
DAG |
Approved |
no |
|
| |
Call Number |
Admin @ si @ JTV2010 |
Serial |
2404 |
|
| Permanent link to this record |
