|
|
Marçal Rusiñol and Josep Llados. 2009. Logo Spotting by a Bag-of-words Approach for Document Categorization. 10th International Conference on Document Analysis and Recognition.111–115.
Abstract: In this paper we present a method for document categorization which processes incoming document images such as invoices or receipts. The categorization of these document images is done in terms of the presence of a certain graphical logo detected without segmentation. The graphical logos are described by a set of local features and the categorization of the documents is performed by the use of a bag-of-words model. Spatial coherence rules are added to reinforce the correct category hypothesis, aiming also to spot the logo inside the document image. Experiments which demonstrate the effectiveness of this system on a large set of real data are presented.
|
|
|
|
Lluis Pere de las Heras, Oriol Ramos Terrades and Josep Llados. 2017. Ontology-Based Understanding of Architectural Drawings. International Workshop on Graphics Recognition. GREC 2015.Graphic Recognition. Current Trends and Challenges.75–85. (LNCS.)
Abstract: In this paper we present a knowledge base of architectural documents aiming at improving existing methods of floor plan classification and understanding. It consists of an ontological definition of the domain and the inclusion of real instances coming from both, automatically interpreted and manually labeled documents. The knowledge base has proven to be an effective tool to structure our knowledge and to easily maintain and upgrade it. Moreover, it is an appropriate means to automatically check the consistency of relational data and a convenient complement of hard-coded knowledge interpretation systems.
Keywords: Graphics recognition; Floor plan analysi; Domain ontology
|
|
|
|
Nuria Cirera, Alicia Fornes, Volkmar Frinken and Josep Llados. 2013. Hybrid grammar language model for handwritten historical documents recognition. 6th Iberian Conference on Pattern Recognition and Image Analysis. Springer Berlin Heidelberg, 117–124. (LNCS.)
Abstract: In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate.
|
|
|
|
Francisco Cruz and Oriol Ramos Terrades. 2013. Handwritten Line Detection via an EM Algorithm. 12th International Conference on Document Analysis and Recognition.718–722.
Abstract: In this paper we present a handwritten line segmentation method devised to work on documents composed of several paragraphs with multiple line orientations. The method is based on a variation of the EM algorithm for the estimation of a set of regression lines between the connected components that compose the image. We evaluated our method on the ICDAR2009 handwriting segmentation contest dataset with promising results that overcome most of the presented methods. In addition, we prove the usability of the presented method by performing line segmentation on the George Washington database obtaining encouraging results.
|
|
|
|
Alicia Fornes, Josep Llados, Joan Mas, Joana Maria Pujadas-Mora and Anna Cabre. 2014. A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts. Digital Access to Textual Cultural Heritage Conference.103–108.
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.
|
|
|
|
Francisco Cruz and Oriol Ramos Terrades. 2012. Document segmentation using relative location features. 21st International Conference on Pattern Recognition.1562–1565.
Abstract: In this paper we evaluate the use of Relative Location Features (RLF) on a historical document segmentation task, and compare the quality of the results obtained on structured and unstructured documents using RLF and not using them. We prove that using these features improve the final segmentation on documents with a strong structure, while their application on unstructured documents does not show significant improvement. Although this paper is not focused on segmenting unstructured documents, results obtained on a benchmark dataset are equal or even overcome previous results of similar works.
|
|
|
|
David Fernandez, Pau Riba, Alicia Fornes and Josep Llados. 2014. On the Influence of Key Point Encoding for Handwritten Word Spotting. 14th International Conference on Frontiers in Handwriting Recognition.476–481.
Abstract: In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries.
Keywords: Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis
|
|
|
|
Salim Jouili, Salvatore Tabbone and Ernest Valveny. 2009. Evaluation of graph matching measures for documents retrieval. In proceedings of 8th IAPR International Workshop on Graphics Recognition.13–21.
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.
Keywords: Graph Matching; Graph retrieval; structural representation; Performance Evaluation
|
|
|
|
Salim Jouili, Salvatore Tabbone and Ernest Valveny. 2010. Comparing Graph Similarity Measures for Graphical Recognition. Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers. Springer Berlin Heidelberg, 37–48. (LNCS.)
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.
|
|
|
|
Salim Jouili, Salvatore Tabbone and Ernest Valveny. 2009. Comparing Graph Similarity Measures for Graphical Recognition. 8th IAPR International Workshop on Graphics Recognition. Springer. (LNCS.)
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.
|
|
