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Author |
Herve Locteau; Sebastien Mace; Ernest Valveny; Salvatore Tabbone |
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Title |
Extraction des pieces de un plan de habitation |
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Conference Article |
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2010 |
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Colloque Internacional Francophone de l´Ecrit et le Document |
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1–12 |
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In this article, a method to extract the rooms of an architectural floor plan image is described. We first present a line detection algorithm to extract long lines in the image. Those lines are analyzed to identify the existing walls. From this point, room extraction can be seen as a classical segmentation task for which each region corresponds to a room. The chosen resolution strategy consists in recursively decomposing the image until getting nearly convex regions. The notion of convexity is difficult to quantify, and the selection of separation lines can also be rough. Thus, we take advantage of knowledge associated to architectural floor plans in order to obtain mainly rectangular rooms. Preliminary tests on a set of real documents show promising results. |
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Sousse, Tunisia |
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CIFED |
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DAG @ dag @ LMV2010 |
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1440 |
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Author |
Jaume Gibert; Ernest Valveny |
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Title |
Graph Embedding based on Nodes Attributes Representatives and a Graph of Words Representation. |
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Conference Article |
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Year |
2010 |
Publication |
13th International worshop on structural and syntactic pattern recognition and 8th international worshop on statistical pattern recognition |
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6218 |
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223–232 |
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Although graph embedding has recently been used to extend statistical pattern recognition techniques to the graph domain, some existing embeddings are usually computationally expensive as they rely on classical graph-based operations. In this paper we present a new way to embed graphs into vector spaces by first encapsulating the information stored in the original graph under another graph representation by clustering the attributes of the graphs to be processed. This new representation makes the association of graphs to vectors an easy step by just arranging both node attributes and the adjacency matrix in the form of vectors. To test our method, we use two different databases of graphs whose nodes attributes are of different nature. A comparison with a reference method permits to show that this new embedding is better in terms of classification rates, while being much more faster. |
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Springer Berlin Heidelberg |
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In E.R. Hancock, R.C. Wilson, T. Windeatt, I. Ulusoy and F. Escolano, |
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0302-9743 |
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978-3-642-14979-5 |
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S+SSPR |
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DAG @ dag @ GiV2010 |
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1416 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis |
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Conference Article |
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2010 |
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15th Iberoamerican Congress on Pattern Recognition |
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6419 |
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30–37 |
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Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation. |
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Sao Paulo, Brazil |
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0302-9743 |
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978-3-642-16686-0 |
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CIARP |
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DAG @ dag @ GVB2010 |
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1462 |
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Author |
Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds) |
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Title |
Graphics Recognition: Achievements, Challenges, and Evolution |
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2010 |
Publication |
8th International Workshop GREC 2009. |
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6020 |
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La Rochelle |
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Springer Link |
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Jean-Marc Ogier; Wenyin Liu; Josep Llados |
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Lecture Notes in Computer Science |
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978-3-642-13727-3 |
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GREC |
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Admin @ si @ OLL2010 |
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1976 |
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Author |
Joan Mas |
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Title |
A Syntactic Pattern Recognition Approach based on a Distribution Tolerant Adjacency Grammar and a Spatial Indexed Parser. Application to Sketched Document Recognition |
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2010 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Sketch recognition is a discipline which has gained an increasing interest in the last
20 years. This is due to the appearance of new devices such as PDA, Tablet PC’s
or digital pen & paper protocols. From the wide range of sketched documents we
focus on those that represent structured documents such as: architectural floor-plans,
engineering drawing, UML diagrams, etc. To recognize and understand these kinds
of documents, first we have to recognize the different compounding symbols and then
we have to identify the relations between these elements. From the way that a sketch
is captured, there are two categories: on-line and off-line. On-line input modes refer
to draw directly on a PDA or a Tablet PC’s while off-line input modes refer to scan
a previously drawn sketch.
This thesis is an overlapping of three different areas on Computer Science: Pattern
Recognition, Document Analysis and Human-Computer Interaction. The aim of this
thesis is to interpret sketched documents independently on whether they are captured
on-line or off-line. For this reason, the proposed approach should contain the following
features. First, as we are working with sketches the elements present in our input
contain distortions. Second, as we would work in on-line or off-line input modes, the
order in the input of the primitives is indifferent. Finally, the proposed method should
be applied in real scenarios, its response time must be slow.
To interpret a sketched document we propose a syntactic approach. A syntactic
approach is composed of two correlated components: a grammar and a parser. The
grammar allows describing the different elements on the document as well as their
relations. The parser, given a document checks whether it belongs to the language
generated by the grammar or not. Thus, the grammar should be able to cope with
the distortions appearing on the instances of the elements. Moreover, it would be
necessary to define a symbol independently of the order of their primitives. Concerning to the parser when analyzing 2D sentences, it does not assume an order in the
primitives. Then, at each new primitive in the input, the parser searches among the
previous analyzed symbols candidates to produce a valid reduction.
Taking into account these features, we have proposed a grammar based on Adjacency Grammars. This kind of grammars defines their productions as a multiset
of symbols rather than a list. This allows describing a symbol without an order in
their components. To cope with distortion we have proposed a distortion model.
This distortion model is an attributed estimated over the constraints of the grammar and passed through the productions. This measure gives an idea on how far is the
symbol from its ideal model. In addition to the distortion on the constraints other
distortions appear when working with sketches. These distortions are: overtracing,
overlapping, gaps or spurious strokes. Some grammatical productions have been defined to cope with these errors. Concerning the recognition, we have proposed an
incremental parser with an indexation mechanism. Incremental parsers analyze the
input symbol by symbol given a response to the user when a primitive is analyzed.
This makes incremental parser suitable to work in on-line as well as off-line input
modes. The parser has been adapted with an indexation mechanism based on a spatial division. This indexation mechanism allows setting the primitives in the space
and reducing the search to a neighbourhood.
A third contribution is a grammatical inference algorithm. This method given a
set of symbols captures the production describing it. In the field of formal languages,
different approaches has been proposed but in the graphical domain not so much work
is done in this field. The proposed method is able to capture the production from
a set of symbol although they are drawn in different order. A matching step based
on the Haussdorff distance and the Hungarian method has been proposed to match
the primitives of the different symbols. In addition the proposed approach is able to
capture the variability in the parameters of the constraints.
From the experimental results, we may conclude that we have proposed a robust
approach to describe and recognize sketches. Moreover, the addition of new symbols
to the alphabet is not restricted to an expert. Finally, the proposed approach has
been used in two real scenarios obtaining a good performance. |
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Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
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Editor |
Gemma Sanchez;Josep Llados |
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978-84-937261-4-0 |
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Call Number |
DAG @ dag @ Mas2010 |
Serial |
1334 |
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Author |
Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
SSP: Sketching slide Presentations, a Syntactic Approach |
Type |
Book Chapter |
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Year |
2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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118-129 |
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The design of a slide presentation is a creative process. In this process first, humans visualize in their minds what they want to explain. Then, they have to be able to represent this knowledge in an understandable way. There exists a lot of commercial software that allows to create our own slide presentations but the creativity of the user is rather limited. In this article we present an application that allows the user to create and visualize a slide presentation from a sketch. A slide may be seen as a graphical document or a diagram where its elements are placed in a particular spatial arrangement. To describe and recognize slides a syntactic approach is proposed. This approach is based on an Adjacency Grammar and a parsing methodology to cope with this kind of grammars. The experimental evaluation shows the performance of our methodology from a qualitative and a quantitative point of view. Six different slides containing different number of symbols, from 4 to 7, have been given to the users and they have drawn them without restrictions in the order of the elements. The quantitative results give an idea on how suitable is our methodology to describe and recognize the different elements in a slide. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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GREC |
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MSL2010 |
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2405 |
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Author |
Joan Mas; Josep Llados; Gemma Sanchez; J.A. Jorge |
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Title |
A syntactic approach based on distortion-tolerant Adjacency Grammars and a spatial-directed parser to interpret sketched diagrams |
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Journal Article |
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2010 |
Publication |
Pattern Recognition |
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PR |
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43 |
Issue |
12 |
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4148–4164 |
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Syntactic Pattern Recognition; Symbol recognition; Diagram understanding; Sketched diagrams; Adjacency Grammars; Incremental parsing; Spatial directed parsing |
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This paper presents a syntactic approach based on Adjacency Grammars (AG) for sketch diagram modeling and understanding. Diagrams are a combination of graphical symbols arranged according to a set of spatial rules defined by a visual language. AG describe visual shapes by productions defined in terms of terminal and non-terminal symbols (graphical primitives and subshapes), and a set functions describing the spatial arrangements between symbols. Our approach to sketch diagram understanding provides three main contributions. First, since AG are linear grammars, there is a need to define shapes and relations inherently bidimensional using a sequential formalism. Second, our parsing approach uses an indexing structure based on a spatial tessellation. This serves to reduce the search space when finding candidates to produce a valid reduction. This allows order-free parsing of 2D visual sentences while keeping combinatorial explosion in check. Third, working with sketches requires a distortion model to cope with the natural variations of hand drawn strokes. To this end we extended the basic grammar with a distortion measure modeled on the allowable variation on spatial constraints associated with grammar productions. Finally, the paper reports on an experimental framework an interactive system for sketch analysis. User tests performed on two real scenarios show that our approach is usable in interactive settings. |
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Elsevier |
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DAG @ dag @ MLS2010 |
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1336 |
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Author |
Jose Antonio Rodriguez; Florent Perronnin; Gemma Sanchez; Josep Llados |
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Title |
Unsupervised writer adaptation of whole-word HMMs with application to word-spotting |
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Journal Article |
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Year |
2010 |
Publication |
Pattern Recognition Letters |
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PRL |
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31 |
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8 |
Pages |
742–749 |
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Word-spotting; Handwriting recognition; Writer adaptation; Hidden Markov model; Document analysis |
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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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Elsevier |
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DAG @ dag @ RPS2010 |
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1290 |
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Author |
Marçal Rusiñol; Josep Llados |
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Title |
Efficient Logo Retrieval Through Hashing Shape Context Descriptors |
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Conference Article |
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2010 |
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9th IAPR International Workshop on Document Analysis Systems |
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215–222 |
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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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Boston; USA |
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DAS |
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DAG @ dag @ RuL2010b |
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1434 |
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Author |
Marçal Rusiñol; Josep Llados |
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Title |
Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections |
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2010 |
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Symbol Spotting in Digital Libraries:Focused Retrieval over Graphic-rich Document Collections |
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Focused Retrieval , Graphical Pattern Indexation,Graphics Recognition ,Pattern Recognition , Performance Evaluation , Symbol Description ,Symbol Spotting |
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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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Springer |
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978-1-84996-208-7 |
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DAG @ dag @ RuL2010a |
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1292 |
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