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Marçal Rusiñol, & Josep Llados. (2007). A Region-Based Hashing Approach for Symbol Spotting in Thechnical Documents. In J.M. Ogier W. L. J. Llados (Ed.), Seventh IAPR International Workshop on Graphics Recognition (41–42).
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Marçal Rusiñol, & Josep Llados. (2006). Symbol Spotting in Technical Drawings Using Vectorial Signatures. In Graphics Recognition: Ten Years Review and Future Perspectives, W. Liu, J. Llados (Eds.), LNCS 3926: 35–46.
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Marçal Rusiñol, & Josep Llados. (2005). Symbol Spotting in Technical Drawings Using Vectorial Signatures.
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Oriol Ramos Terrades, Salvatore Tabbone, L. Wendling, & Ernest Valveny. (2004). Symbol Recognition based on a Multiresolution Analysis of the Radon Transform.
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Oriol Ramos Terrades, Salvatore Tabbone, & Ernest Valveny. (2007). A Review of Shape Descriptors for Document Analysis. In 9th International Conference on Document Analysis and Recognition (Vol. 1, 227–231).
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Oriol Ramos Terrades, Salvatore Tabbone, & Ernest Valveny. (2007). Optimal Linear Combination for Two-class Classifiers. In Proceedings of the International Conference on Advances in Pattern Recognition.
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Oriol Ramos Terrades, Salvatore Tabbone, & Ernest Valveny. (2006). Combination of shape descriptors using an adaptation of boosting.
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Jose Antonio Rodriguez, Gemma Sanchez, & Josep Llados. (2008). Categorization of Digital Ink Elements using Spectral Features. In J.M. Ogier J. L. W. Liu (Ed.), Graphics Recognition: Recent Advances and New Opportunities (Vol. 5046, 188–198). LNCS. Springer–Verlag.
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Jose Antonio Rodriguez, Gemma Sanchez, & Josep Llados. (2007). Categorization of Digital Ink Elements using Spectral Features. In Seventh IAPR International Workshop on Graphics Recognition (63–64).
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Jose Antonio Rodriguez, Gemma Sanchez, & Josep Llados. (2007). A Pen-based Interface for Real-time Document Edition. In 9th International Conference on Document Analysis and Recognition. (Vol. 2, 939–944).
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Jose Antonio Rodriguez, Gemma Sanchez, & Josep Llados. (2007). Rejection strategies involving classifier combination for handwriting recognition. In 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:97–104.
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Jose Antonio Rodriguez, Gemma Sanchez, & Josep Llados. (2006). Automatic Interpretation of Proofreading Sketches.
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Jose Antonio Rodriguez, Florent Perronnin, Gemma Sanchez, & Josep Llados. (2010). Unsupervised writer adaptation of whole-word HMMs with application to word-spotting. PRL - Pattern Recognition Letters, 31(8), 742–749.
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.
Keywords: Word-spotting; Handwriting recognition; Writer adaptation; Hidden Markov model; Document analysis
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Jose Antonio Rodriguez, Florent Perronnin, Gemma Sanchez, & Josep Llados. (2008). Unsupervised writer style adaptation for handwritten word spotting. In Pattern Recognition. 19th International Conference on, IBM Best Student Paper Award..
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Partha Pratim Roy, Umapada Pal, & Josep Llados. (2010). Query Driven Word Retrieval in Graphical Documents. In 9th IAPR International Workshop on Document Analysis Systems (191–198).
Abstract: In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents.
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