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Jaume Gibert, Ernest Valveny and Horst Bunke. 2011. Vocabulary Selection for Graph of Words Embedding. In Vitria, J., J.M.R. Sanches and M. Hernández, eds. 5th Iberian Conference on Pattern Recognition and Image Analysis. Berlin, Springer, 216–223. (LNCS.)
Abstract: The Graph of Words Embedding consists in mapping every graph in a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. It has been shown to perform well for graphs with discrete label alphabets. In this paper we extend the methodology to graphs with n-dimensional continuous attributes by selecting node representatives. We propose three different discretization procedures for the attribute space and experimentally evaluate the dependence on both the selector and the number of node representatives. In the context of graph classification, the experimental results reveal that on two out of three public databases the proposed extension achieves superior performance over a standard reference system.
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Albert Gordo. 2009. A Cyclic Page Layout Descriptor for Document Classification & Retrieval. (Master's thesis, .)
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Farshad Nourbakhsh. 2009. Colour logo recognition. (Master's thesis, .)
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Debora Gil, Jordi Gonzalez and Gemma Sanchez, eds. 2007. Computer Vision: Advances in Research and Development. Bellaterra (Spain), UAB. (2.)
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Agnes Borras. 2009. Contributions to the Content-Based Image Retrieval Using Pictorial Queries. (Ph.D. thesis, Ediciones Graficas Rey.)
Abstract: The broad access to digital cameras, personal computers and Internet, has lead to the generation of large volumes of data in digital form. If we want an effective usage of this huge amount of data, we need automatic tools to allow the retrieval of relevant information. Image data is a particular type of information that requires specific techniques of description and indexing. The computer vision field that studies these kind of techniques is called Content-Based Image Retrieval (CBIR). Instead of using text-based descriptions, a system of CBIR deals on properties that are inherent in the images themselves. Hence, the feature-based description provides a universal via of image expression in contrast with the more than 6000 languages spoken in the world.
Nowadays, the CBIR is a dynamic focus of research that has derived in important applications for many professional groups. The potential fields of application can be such diverse as: the medical domain, the crime prevention, the protection of the intel- lectual property, the journalism, the graphic design, the web search, the preservation of cultural heritage, etc.
The definition on the role of the user is a key point in the development of a CBIR application. The user is in charge to formulate the queries from which the images are retrieved. We have centered our attention on the image retrieval techniques that use queries based on pictorial information. We have identified a taxonomy composed by four main query paradigms: query-by-selection, query-by-iconic-composition, query- by-sketch and query-by-paint. Each one of these paradigms allows a different degree of user expressivity. From a simple image selection, to a complete painting of the query, the user takes control of the input in the CBIR system.
Along the chapters of this thesis we have analyzed the influence that each query paradigm imposes in the internal operations of a CBIR system. Moreover, we have proposed a set of contributions that we have exemplified in the context of a final application.
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Ernest Valveny and Enric Marti. 1999. Application of deformable template matching to symbol recognition in hand-written architectural draw. Proceedings of the Fifth International Conference on. Bangalore (India).
Abstract: We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified.
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Josep Llados, J. Lopez-Krahe and Enric Marti. 1999. A Hough-based method for hatched pattern detection in maps and diagrams..
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Josep Llados, Felipe Lumbreras and X. Varona. 1999. A multidocument platform for automatic reading of identity cards..
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A. Pujol and 6 others. 1999. Real time pharmaceutical product recognition using color and shape indexing. Proceedings of the 2nd International Workshop on European Scientific and Industrial Collaboration (WESIC´99), Promotoring Advanced Technologies in Manufacturing..
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Josep Llados, Gemma Sanchez and Enric Marti. 1997. A String-Based Method to Recognize Symbols and Structural Textures in Architectural Plans..
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