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Author Sebastien Mace; Herve Locteau; Ernest Valveny; Salvatore Tabbone
Title A system to detect rooms in architectural floor plan images Type Conference Article
Year 2010 Publication 9th IAPR International Workshop on Document Analysis Systems Abbreviated Journal
Volume Issue (up) Pages 167–174
Keywords
Abstract In this article, a system to detect rooms in architectural floor plan images is described. We first present a primitive extraction algorithm for line detection. It is based on an original coupling of classical Hough transform with image vectorization in order to perform robust and efficient line detection. We show how the lines that satisfy some graphical arrangements are combined into walls. We also present the way we detect some door hypothesis thanks to the extraction of arcs. Walls and door hypothesis are then used by our room segmentation strategy; it 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 between regions can also be rough. We take advantage of knowledge associated to architectural floor plans in order to obtain mostly rectangular rooms. Qualitative and quantitative evaluations performed on a corpus of real documents show promising results.
Address Boston; USA
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-60558-773-8 Medium
Area Expedition Conference DAS
Notes DAG Approved no
Call Number DAG @ dag @ MLV2010 Serial 1437
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Author Herve Locteau; Sebastien Mace; Ernest Valveny; Salvatore Tabbone
Title Extraction des pieces de un plan de habitation Type Conference Article
Year 2010 Publication Colloque Internacional Francophone de l´Ecrit et le Document Abbreviated Journal
Volume Issue (up) Pages 1–12
Keywords
Abstract 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.
Address Sousse, Tunisia
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference CIFED
Notes DAG Approved no
Call Number DAG @ dag @ LMV2010 Serial 1440
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Author Joan Mas; Gemma Sanchez; Josep Llados
Title SSP: Sketching slide Presentations, a Syntactic Approach Type Conference Article
Year 2009 Publication 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue (up) Pages
Keywords
Abstract 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.
Address La Rochelle; France; July 2009
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number DAG @ dag @ MSL2009a Serial 1441
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Author Salim Jouili; Salvatore Tabbone; Ernest Valveny
Title Comparing Graph Similarity Measures for Graphical Recognition. Type Conference Article
Year 2009 Publication 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue (up) Pages
Keywords
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.
Address La Rochelle; France; July 2009
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number DAG @ dag @ JTV2009 Serial 1442
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Author Mathieu Nicolas Delalandre; Jean-Yves Ramel; Ernest Valveny; Muhammad Muzzamil Luqman
Title A Performance Characterization Algorithm for Symbol Localization Type Conference Article
Year 2009 Publication 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue (up) Pages 3-11
Keywords
Abstract In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more “reliable” and “open” solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [1], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
Address La Rochelle; July 2009
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number DAG @ dag @ DRV2009 Serial 1443
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Author Marçal Rusiñol; K. Bertet; Jean-Marc Ogier; Josep Llados
Title Symbol Recognition Using a Concept Lattice of Graphical Patterns Type Conference Article
Year 2009 Publication 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue (up) Pages
Keywords
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.
Address La Rochelle; July 2009
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number DAG @ dag @ RBO2009 Serial 1444
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Author Partha Pratim Roy; Umapada Pal; Josep Llados
Title Touching Text Character Localization in Graphical Documents using SIFT Type Conference Article
Year 2009 Publication In proceedings 8th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue (up) Pages
Keywords
Abstract Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches.
Address La rochelle; July 2009
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference GREC
Notes DAG Approved no
Call Number DAG @ dag @ RPL2009c Serial 1445
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Author Carlo Gatta; Simone Balocco; Francesco Ciompi; R. Hemetsberger; Oriol Rodriguez-Leor; Petia Radeva
Title Real-time gating of IVUS sequences based on motion blur analysis: Method and quantitative validation Type Conference Article
Year 2010 Publication 13th international conference on Medical image computing and computer-assisted intervention Abbreviated Journal
Volume II Issue (up) Pages 59-67
Keywords
Abstract Intravascular Ultrasound (IVUS) is an image-guiding technique for cardiovascular diagnostic, providing cross-sectional images of vessels. During the acquisition, the catheter is pulled back (pullback) at a constant speed in order to acquire spatially subsequent images of the artery. However, during this procedure, the heart twist produces a swinging fluctuation of the probe position along the vessel axis. In this paper we propose a real-time gating algorithm based on the analysis of motion blur variations during the IVUS sequence. Quantitative tests performed on an in-vitro ground truth data base shown that our method is superior to state of the art algorithms both in computational speed and accuracy.
Address
Corporate Author Thesis
Publisher Springer-Verlag Berlin Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MICCAI
Notes MILAB Approved no
Call Number BCNPCL @ bcnpcl @ GBC2010 Serial 1447
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Author Eloi Puertas; Sergio Escalera; Oriol Pujol
Title Classifying Objects at Different Sizes with Multi-Scale Stacked Sequential Learning Type Conference Article
Year 2010 Publication 13th International Conference of the Catalan Association for Artificial Intelligence Abbreviated Journal
Volume 220 Issue (up) Pages 193–200
Keywords
Abstract Sequential learning is that discipline of machine learning that deals with dependent data. In this paper, we use the Multi-scale Stacked Sequential Learning approach (MSSL) to solve the task of pixel-wise classification based on contextual information. The main contribution of this work is a shifting technique applied during the testing phase that makes possible, thanks to template images, to classify objects at different sizes. The results show that the proposed method robustly classifies such objects capturing their spatial relationships.
Address
Corporate Author Thesis
Publisher Place of Publication Editor R. Alquezar, A. Moreno, J. Aguilar
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-1-60750-642-3 Medium
Area Expedition Conference CCIA
Notes HUPBA;MILAB Approved no
Call Number BCNPCL @ bcnpcl @ PEP2010 Serial 1448
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Author Sergio Escalera; Oriol Pujol; Eric Laciar; Jordi Vitria; Esther Pueyo; Petia Radeva
Title Classification of Coronary Damage in Chronic Chagasic Patients Type Book Chapter
Year 2010 Publication Intelligent Systems – From Theory to Practice. Studies in Computational Intelligence Abbreviated Journal
Volume 299 Issue (up) Pages 461-478
Keywords Chagas disease; Error-Correcting Output Codes; High resolution ECG; Decoding
Abstract Post Conference IEEE-IS 2008
The Chagas’ disease is endemic in all Latin America, affecting millions of people in the continent. In order to diagnose and treat the chagas’ disease, it is important to detect and measure the coronary damage of the patient. In this paper,
we analyze and categorize patients into different groups based on the coronary damage produced by the disease. Based on the features of the heart cycle extracted using high resolution ECG, a multi-class scheme of Error-Correcting Output Codes (ECOC)is formulated and successfully applied. The results show that the proposed scheme obtains significant performance improvements compared to previous works and state-of-the-art ECOC designs.
Address
Corporate Author Thesis
Publisher Springer-Verlag Place of Publication Editor V. Sgurev, M. Hadjiski (eds)
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;MILAB;HUPBA;MV Approved no
Call Number BCNPCL @ bcnpcl @ EPL2010 Serial 1452
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Author Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva
Title Conditional Random Fields for image segmentation in Intravascular Ultrasound Type Conference Article
Year 2010 Publication Medical Image Computing in Catalunya: Graduate Student Workshop Abbreviated Journal
Volume Issue (up) Pages 13–14
Keywords
Abstract We present a Conditional Random Fields based approach for segmenting Intravascular Ultrasond (IVUS) images. The presented method uses a contextual discriminative graphical model to deal with the presence of distorsions and artifacts in IVUS images, that turns the segmentation of interesting regions into a difficult task. An accurate lumen segmentation on IVUS longitudinal images is achieved.
Address Girona
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MICCAT
Notes MILAB;HUPBA Approved no
Call Number BCNPCL @ bcnpcl @ CPF2010 Serial 1453
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Author Jose Manuel Alvarez
Title Combining Context and Appearance for Road Detection Type Book Whole
Year 2010 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue (up) Pages
Keywords
Abstract Road traffic crashes have become a major cause of death and injury throughout the world.
Hence, in order to improve road safety, the automobile manufacture is moving towards the
development of vehicles with autonomous functionalities such as keeping in the right lane, safe distance keeping between vehicles or regulating the speed of the vehicle according to the traffic conditions. A key component of these systems is vision–based road detection that aims to detect the free road surface ahead the moving vehicle. Detecting the road using a monocular vision system is very challenging since the road is an outdoor scenario imaged from a mobile platform. Hence, the detection algorithm must be able to deal with continuously changing imaging conditions such as the presence ofdifferent objects (vehicles, pedestrians), different environments (urban, highways, off–road), different road types (shape, color), and different imaging conditions (varying illumination, different viewpoints and changing weather conditions). Therefore, in this thesis, we focus on vision–based road detection using a single color camera. More precisely, we first focus on analyzing and grouping pixels according to their low–level properties. In this way, two different approaches are presented to exploit
color and photometric invariance. Then, we focus the research of the thesis on exploiting context information. This information provides relevant knowledge about the road not using pixel features from road regions but semantic information from the analysis of the scene.
In this way, we present two different approaches to infer the geometry of the road ahead
the moving vehicle. Finally, we focus on combining these context and appearance (color)
approaches to improve the overall performance of road detection algorithms. The qualitative and quantitative results presented in this thesis on real–world driving sequences show that the proposed method is robust to varying imaging conditions, road types and scenarios going beyond the state–of–the–art.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Antonio Lopez;Theo Gevers
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-937261-8-8 Medium
Area Expedition Conference
Notes ADAS Approved no
Call Number Admin @ si @ Alv2010 Serial 1454
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Author Partha Pratim Roy
Title Multi-Oriented and Multi-Scaled Text Character Analysis and Recognition in Graphical Documents and their Applications to Document Image Retrieval Type Book Whole
Year 2010 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue (up) Pages
Keywords
Abstract With the advent research of Document Image Analysis and Recognition (DIAR), an
important line of research is explored on indexing and retrieval of graphics rich documents. It aims at finding relevant documents relying on segmentation and recognition
of text and graphics components underlying in non-standard layout where commercial
OCRs can not be applied due to complexity. This thesis is focused towards text information extraction approaches in graphical documents and retrieval of such documents
using text information.
Automatic text recognition in graphical documents (map, engineering drawing,
etc.) involves many challenges because text characters are usually printed in multioriented and multi-scale way along with different graphical objects. Text characters
are used to annotate the graphical curve lines and hence, many times they follow
curvi-linear paths too. For OCR of such documents, individual text lines and their
corresponding words/characters need to be extracted.
For recognition of multi-font, multi-scale and multi-oriented characters, we have
proposed a feature descriptor for character shape using angular information from contour pixels to take care of the invariance nature. To improve the efficiency of OCR, an
approach towards the segmentation of multi-oriented touching strings into individual
characters is also discussed. Convex hull based background information is used to
segment a touching string into possible primitive segments and later these primitive
segments are merged to get optimum segmentation using dynamic programming. To
overcome the touching/overlapping problem of text with graphical lines, a character
spotting approach using SIFT and skeleton information is included. Afterwards, we
propose a novel method to extract individual curvi-linear text lines using the foreground and background information of the characters of the text and a water reservoir
concept is used to utilize the background information.
We have also formulated the methodologies for graphical document retrieval applications using query words and seals. The retrieval approaches are performed using
recognition results of individual components in the document. Given a query text,
the system extracts positional knowledge from the query word and uses the same to
generate hypothetical locations in the document. Indexing of documents is also performed based on automatic detection of seals from documents containing cluttered
background. A seal is characterized by scale and rotation invariant spatial feature
descriptors computed from labelled text characters and a concept based on the Generalized Hough Transform is used to locate the seal in documents.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Josep Llados;Umapada Pal
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 978-84-937261-7-1 Medium
Area Expedition Conference
Notes Approved no
Call Number Admin @ si @ Roy2010 Serial 1455
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Author Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard
Title A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume 6388 Issue (up) Pages 93–98
Keywords
Abstract We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR.
Address
Corporate Author Thesis
Publisher Springer, Heidelberg Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN 0302-9743 ISBN 978-3-642-17710-1 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number DAG @ dag @ LLR2010 Serial 1459
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Author Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados
Title A Content Spotting System For Line Drawing Graphic Document Images Type Conference Article
Year 2010 Publication 20th International Conference on Pattern Recognition Abbreviated Journal
Volume 20 Issue (up) Pages 3420–3423
Keywords
Abstract We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1051-4651 ISBN 978-1-4244-7542-1 Medium
Area Expedition Conference ICPR
Notes DAG Approved no
Call Number DAG @ dag @ LBR2010b Serial 1460
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