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| Author | Oriol Ramos Terrades; Ernest Valveny; Salvatore Tabbone | ||||
| Title | Optimal Classifier Fusion in a Non-Bayesian Probabilistic Framework | Type | Journal Article | ||
| Year | 2009 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence | Abbreviated Journal | TPAMI |
| Volume | 31 | Issue | 9 | Pages | 1630–1644 |
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| Abstract | The combination of the output of classifiers has been one of the strategies used to improve classification rates in general purpose classification systems. Some of the most common approaches can be explained using the Bayes' formula. In this paper, we tackle the problem of the combination of classifiers using a non-Bayesian probabilistic framework. This approach permits us to derive two linear combination rules that minimize misclassification rates under some constraints on the distribution of classifiers. In order to show the validity of this approach we have compared it with other popular combination rules from a theoretical viewpoint using a synthetic data set, and experimentally using two standard databases: the MNIST handwritten digit database and the GREC symbol database. Results on the synthetic data set show the validity of the theoretical approach. Indeed, results on real data show that the proposed methods outperform other common combination schemes. | ||||
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| ISSN | 0162-8828 | ISBN | Medium | ||
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DAG | Approved | no | ||
| Call Number | DAG @ dag @ RVT2009 | Serial | 1220 | ||
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| Author | Ricard Coll; Alicia Fornes; Josep Llados | ||||
| Title | Graphological Analysis of Handwritten Text Documents for Human Resources Recruitment | Type | Conference Article | ||
| Year | 2009 | Publication | 10th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1081–1085 | ||
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| Abstract | The use of graphology in recruitment processes has become a popular tool in many human resources companies. This paper presents a model that links features from handwritten images to a number of personality characteristics used to measure applicant aptitudes for the job in a particular hiring scenario. In particular we propose a model of measuring active personality and leadership of the writer. Graphological features that define such a profile are measured in terms of document and script attributes like layout configuration, letter size, shape, slant and skew angle of lines, etc. After the extraction, data is classified using a neural network. An experimental framework with real samples has been constructed to illustrate the performance of the approach. | ||||
| Address | Barcelona, Spain | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | 978-1-4244-4500-4 | Medium | |
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ CFL2009 | Serial | 1221 | ||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke | ||||
| Title | Symbol-independent writer identification in old handwritten music scores | Type | Conference Article | ||
| Year | 2009 | Publication | In proceedings of 8th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 186–197 | ||
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| Address | La Rochelle, France | ||||
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| Publisher | Springer Berlin Heidelberg | Place of Publication | Editor | ||
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| 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 @ FLS2009a | Serial | 1222 | ||
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| Author | Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke | ||||
| Title | On the use of textural features for writer identification in old handwritten music scores | Type | Conference Article | ||
| Year | 2009 | Publication | 10th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 996 - 1000 | ||
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| Abstract | Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores which uses only music notation to determine the author. The steps of the proposed system are the following. First of all, the music sheet is preprocessed for obtaining a music score without the staff lines. Afterwards, four different methods for generating texture images from music symbols are applied. Every approach uses a different spatial variation when combining the music symbols to generate the textures. Finally, Gabor filters and Grey-scale Co-ocurrence matrices are used to obtain the features. The classification is performed using a k-NN classifier based on Euclidean distance. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving encouraging identification rates. | ||||
| Address | Barcelona | ||||
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| ISSN | 1520-5363 | ISBN | 978-1-4244-4500-4 | Medium | |
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ FLS2009b | Serial | 1223 | ||
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| Author | Agnes Borras; Josep Llados | ||||
| Title | Corest: A measure of color and space stability to detect salient regions according to human criteria | Type | Conference Article | ||
| Year | 2009 | Publication | 5th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
| Volume | Issue | Pages | 204-209 | ||
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| Address | Lisboa, Portugal | ||||
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| ISSN | ISBN | 978-989-8111-69-2 | Medium | ||
| Area | Expedition | Conference | VISAPP | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ BoL2009 | Serial | 1225 | ||
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| 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 | ||||
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| 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 | ||
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| Author | Partha Pratim Roy; Josep Llados; Umapada Pal | ||||
| Title | A Complete System for Detection and Recognition of Text in Graphical Documents using Background Information | Type | Conference Article | ||
| Year | 2009 | Publication | 5th International Conference on Computer Vision Theory and Applications | Abbreviated Journal | |
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| Address | Lisboa, Portugal | ||||
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| ISSN | ISBN | 978-989-8111-69-2 | Medium | ||
| Area | Expedition | Conference | VISAPP | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ RLP2009 | Serial | 1238 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
| Title | Seal detection and recognition: An approach for document indexing | Type | Conference Article | ||
| Year | 2009 | Publication | 10th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 101–105 | ||
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| Abstract | Reliable indexing of documents having seal instances can be achieved by recognizing seal information. This paper presents a novel approach for detecting and classifying such multi-oriented seals in these documents. First, Hough Transform based methods are applied to extract the seal regions in documents. Next, isolated text characters within these regions are detected. Rotation and size invariant features and a support vector machine based classifier have been used to recognize these detected text characters. Next, for each pair of character, we encode their relative spatial organization using their distance and angular position with respect to the centre of the seal, and enter this code into a hash table. Given an input seal, we recognize the individual text characters and compute the code for pair-wise character based on the relative spatial organization. The code obtained from the input seal helps to retrieve model hypothesis from the hash table. The seal model to which we get maximum hypothesis is selected for the recognition of the input seal. The methodology is tested to index seal in rotation and size invariant environment and we obtained encouraging results. | ||||
| Address | Barcelona, Spain | ||||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | 978-1-4244-4500-4 | Medium | |
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPL2009b | Serial | 1239 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre | ||||
| Title | Multi-Oriented and Multi-Sized Touching Character Segmentation using Dynamic Programming | Type | Conference Article | ||
| Year | 2009 | Publication | 10th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 11–15 | ||
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| Abstract | In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region at the background portion. Using Convex Hull information, we use these background information to find some initial points to segment a touching string into possible primitive segments (a primitive segment consists of a single character or a part of a character). Next these primitive segments are merged to get optimum segmentation and dynamic programming is applied using total likelihood of characters as the objective function. SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment, we obtained encouraging results. | ||||
| Address | Barcelona, Spain | ||||
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| ISSN | 1520-5363 | ISBN | 978-1-4244-4500-4 | Medium | |
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPL2009a | Serial | 1240 | ||
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| Author | Marçal Rusiñol | ||||
| Title | Geometric and Structural-based Symbol Spotting. Application to Focused Retrieval in Graphic Document Collections | Type | Book Whole | ||
| Year | 2009 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Usually, pattern recognition systems consist of two main parts. On the one hand, the data acquisition and, on the other hand, the classification of this data on a certain category. In order to recognize which category a certain query element belongs to, a set of pattern models must be provided beforehand. An off-line learning stage is needed to train the classifier and to offer a robust classification of the patterns. Within the pattern recognition field, we are interested in the recognition of graphics and, in particular, on the analysis of documents rich in graphical information. In this context, one of the main concerns is to see if the proposed systems remain scalable with respect to the data volume so as it can handle growing amounts of symbol models. In order to avoid to work with a database of reference symbols, symbol spotting and on-the-fly symbol recognition methods have been introduced in the past years.
Generally speaking, the symbol spotting problem can be defined as the identification of a set of regions of interest from a document image which are likely to contain an instance of a certain queriedn symbol without explicitly applying the whole pattern recognition scheme. Our application framework consists on indexing a collection of graphic-rich document images. This collection is queried by example with a single instance of the symbol to look for and, by means of symbol spotting methods we retrieve the regions of interest where the symbol is likely to appear within the documents. This kind of applications are known as focused retrieval methods. In order that the focused retrieval application can handle large collections of documents there is a need to provide an efficient access to the large volume of information that might be stored. We use indexing strategies in order to efficiently retrieve by similarity the locations where a certain part of the symbol appears. In that scenario, graphical patterns should be used as indices for accessing and navigating the collection of documents. These indexing mechanism allow the user to search for similar elements using graphical information rather than textual queries. Along this thesis we present a spotting architecture and different methods aiming to build a complete focused retrieval application dealing with a graphic-rich document collections. In addition, a protocol to evaluate the performance of symbol spotting systems in terms of recognition abilities, location accuracy and scalability is proposed. |
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| Address | Barcelona (Spain) | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Josep Llados | |
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| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ Rus2009 | Serial | 1264 | ||
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| Author | Mathieu Nicolas Delalandre; Ernest Valveny; Tony Pridmore; Dimosthenis Karatzas | ||||
| Title | Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems | Type | Journal Article | ||
| Year | 2010 | Publication | International Journal on Document Analysis and Recognition | Abbreviated Journal | IJDAR |
| Volume | 13 | Issue | 3 | Pages | 187-207 |
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| Abstract | This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results. | ||||
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| Publisher | Springer-Verlag | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1433-2833 | ISBN | Medium | ||
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| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ DVP2010 | Serial | 1289 | ||
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| Author | Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados | ||||
| Title | Unsupervised writer adaptation of whole-word HMMs with application to word-spotting | Type | Journal Article | ||
| Year | 2010 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
| Volume | 31 | Issue | 8 | Pages | 742–749 |
| Keywords | Word-spotting; Handwriting recognition; Writer adaptation; Hidden Markov model; Document analysis | ||||
| Abstract | In this paper we propose a novel approach for writer adaptation in a handwritten word-spotting task. The method exploits the fact that the semi-continuous hidden Markov model separates the word model parameters into (i) a codebook of shapes and (ii) a set of word-specific parameters.
Our main contribution is to employ this property to derive writer-specific word models by statistically adapting an initial universal codebook to each document. This process is unsupervised and does not even require the appearance of the keyword(s) in the searched document. Experimental results show an increase in performance when this adaptation technique is applied. To the best of our knowledge, this is the first work dealing with adaptation for word-spotting. The preliminary version of this paper obtained an IBM Best Student Paper Award at the 19th International Conference on Pattern Recognition. |
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| Publisher | Elsevier | Place of Publication | Editor | ||
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| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPS2010 | Serial | 1290 | ||
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| Author | Partha Pratim Roy; Umapada Pal; Josep Llados | ||||
| Title | Seal Object Detection in Document Images using GHT of Local Component Shapes | Type | Conference Article | ||
| Year | 2010 | Publication | 10th ACM Symposium On Applied Computing | Abbreviated Journal | |
| Volume | Issue | Pages | 23–27 | ||
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| Abstract | Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal from documents with cluttered background. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). Recognition of multi-scale and multi-oriented component is done using Support Vector Machine classifier. Generalized Hough Transform (GHT) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal object in a document. Experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents. | ||||
| Address | Sierre, Switzerland | ||||
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| Area | Expedition | Conference | SAC | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ RPL2010a | Serial | 1291 | ||
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| Author | Marçal Rusiñol; Josep Llados | ||||
| Title | Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections | Type | Book Whole | ||
| Year | 2010 | Publication | Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Focused Retrieval , Graphical Pattern Indexation,Graphics Recognition ,Pattern Recognition , Performance Evaluation , Symbol Description ,Symbol Spotting | ||||
| Abstract | The specific problem of symbol recognition in graphical documents requires additional techniques to those developed for character recognition. The most well-known obstacle is the so-called Sayre paradox: Correct recognition requires good segmentation, yet improvement in segmentation is achieved using information provided by the recognition process. This dilemma can be avoided by techniques that identify sets of regions containing useful information. Such symbol-spotting methods allow the detection of symbols in maps or technical drawings without having to fully segment or fully recognize the entire content.
This unique text/reference provides a complete, integrated and large-scale solution to the challenge of designing a robust symbol-spotting method for collections of graphic-rich documents. The book examines a number of features and descriptors, from basic photometric descriptors commonly used in computer vision techniques to those specific to graphical shapes, presenting a methodology which can be used in a wide variety of applications. Additionally, readers are supplied with an insight into the problem of performance evaluation of spotting methods. Some very basic knowledge of pattern recognition, document image analysis and graphics recognition is assumed. |
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| Publisher | Springer | Place of Publication | Editor | ||
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| ISSN | ISBN | 978-1-84996-208-7 | Medium | ||
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| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ RuL2010a | Serial | 1292 | ||
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| Author | Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados | ||||
| Title | Vers une approche foue of encapsulation de graphes: application a la reconnaissance de symboles | Type | Conference Article | ||
| Year | 2010 | Publication | Colloque International Francophone sur l'Écrit et le Document | Abbreviated Journal | |
| Volume | Issue | Pages | 169-184 | ||
| Keywords | Fuzzy interval; Graph embedding; Bayesian network; Symbol recognition | ||||
| Abstract | We present a new methodology for symbol recognition, by employing a structural approach for representing visual associations in symbols and a statistical classifier for recognition. A graphic symbol is vectorized, its topological and geometrical details are encoded by an attributed relational graph and a signature is computed for it. Data adapted fuzzy intervals have been introduced for addressing the sensitivity of structural representations to noise. The joint probability distribution of signatures is encoded by a Bayesian network, which serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures of underlying symbol set, and is deployed in a supervised learning scenario for recognizing query symbols. Experimental results on pre-segmented 2D linear architectural and electronic symbols from GREC databases are presented. | ||||
| Address | Sousse, Tunisia | ||||
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| Area | Expedition | Conference | CIFED | ||
| Notes |
DAG | Approved | no | ||
| Call Number | DAG @ dag @ LBR2010a | Serial | 1293 | ||
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