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Marçal Rusiñol and Josep Llados. 2010. Efficient Logo Retrieval Through Hashing Shape Context Descriptors. 9th IAPR International Workshop on Document Analysis Systems.215–222.
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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Marçal Rusiñol and Josep Llados. 2014. Boosting the Handwritten Word Spotting Experience by Including the User in the Loop. PR, 47(3), 1063–1072.
Abstract: In this paper, we study the effect of taking the user into account in a query-by-example handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and two baseline word spotting approaches both based on the bag-of-visual-words model. We finally present two alternative ways of presenting the results to the user that might be more attractive and suitable to the user's needs than the classic ranked list.
Keywords: Handwritten word spotting; Query by example; Relevance feedback; Query fusion; Multidimensional scaling
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Marçal Rusiñol and Josep Llados. 2012. The Role of the Users in Handwritten Word Spotting Applications: Query Fusion and Relevance Feedback. 13th International Conference on Frontiers in Handwriting Recognition.55–60.
Abstract: In this paper we present the importance of including the user in the loop in a handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and a baseline word spotting approach based on a bag-of-visual-words model.
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Marçal Rusiñol and Josep Llados. 2017. Flowchart Recognition in Patent Information Retrieval. In M. Lupu, K. Mayer, N. Kando and A.J. Trippe, eds. Current Challenges in Patent Information Retrieval. Springer Berlin Heidelberg, 351–368.
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Marçal Rusiñol, Josep Llados and Gemma Sanchez. 2010. Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings. PAA, 13(3), 321–331.
Abstract: In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes.
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Marçal Rusiñol, Josep Llados and Philippe Dosch. 2007. Camera-Based Graphical Symbol Detection. 9th IEEE International Conference on Document Analysis and Recognition.884–888.
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Marçal Rusiñol, K. Bertet, Jean-Marc Ogier and Josep Llados. 2009. Symbol Recognition Using a Concept Lattice of Graphical Patterns. 8th IAPR International Workshop on Graphics Recognition.
Abstract: In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.
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Marçal Rusiñol, K. Bertet, Jean-Marc Ogier and Josep Llados. 2010. Symbol Recognition Using a Concept Lattice of Graphical Patterns. Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers. Springer Berlin Heidelberg, 187–198. (LNCS.)
Abstract: In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.
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Marçal Rusiñol and Lluis Gomez. 2018. Avances en clasificación de imágenes en los últimos diez años. Perspectivas y limitaciones en el ámbito de archivos fotográficos históricos.
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Marçal Rusiñol, Lluis Gomez, A. Landman, M. Silva Constenla and Dimosthenis Karatzas. 2019. Automatic Structured Text Reading for License Plates and Utility Meters. BMVC Workshop on Visual Artificial Intelligence and Entrepreneurship.
Abstract: Reading text in images has attracted interest from computer vision researchers for
many years. Our technology focuses on the extraction of structured text – such as serial
numbers, machine readings, product codes, etc. – so that it is able to center its attention just on the relevant textual elements. It is conceived to work in an end-to-end fashion, bypassing any explicit text segmentation stage. In this paper we present two different industrial use cases where we have applied our automatic structured text reading technology. In the first one, we demonstrate an outstanding performance when reading license plates compared to the current state of the art. In the second one, we present results on our solution for reading utility meters. The technology is commercialized by a recently created spin-off company, and both solutions are at different stages of integration with final clients.
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