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Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Plausibility-Graphs for Symbol Spotting in Graphical Documents |
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Conference Article |
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2013 |
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10th IAPR International Workshop on Graphics Recognition |
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Graph representation of graphical documents often suffers from noise viz. spurious nodes and spurios edges of graph and their discontinuity etc. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance.
But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical
graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset. |
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Bethlehem; PA; USA; August 2013 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.045; 600.056; 600.061; 601.152 |
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Admin @ si @ BDJ2013 |
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2360 |
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Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents |
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Conference Article |
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Year |
2013 |
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12th International Conference on Document Analysis and Recognition |
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1078-1082 |
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This paper deals with a subgraph matching problem in Region Adjacency Graph (RAG) applied to symbol spotting in graphical documents. RAG is a very important, efficient and natural way of representing graphical information with a graph but this is limited to cases where the information is well defined with perfectly delineated regions. What if the information we are interested in is not confined within well defined regions? This paper addresses this particular problem and solves it by defining near convex grouping of oriented line segments which results in near convex regions. Pure convexity imposes hard constraints and can not handle all the cases efficiently. Hence to solve this problem we have defined a new type of convexity of regions, which allows convex regions to have concavity to some extend. We call this kind of regions Near Convex Regions (NCRs). These NCRs are then used to create the Near Convex Region Adjacency Graph (NCRAG) and with this representation we have formulated the problem of symbol spotting in graphical documents as a subgraph matching problem. For subgraph matching we have used the Approximate Edit Distance Algorithm (AEDA) on the neighborhood string, which starts working after finding a key node in the input or target graph and iteratively identifies similar nodes of the query graph in the neighborhood of the key node. The experiments are performed on artificial, real and distorted datasets. |
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Washington; USA; August 2013 |
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1520-5363 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.045; 600.056; 600.061; 601.152 |
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Admin @ si @ DLB2013a |
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2358 |
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Author |
Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
Hierarchical Plausibility-Graphs for Symbol Spotting in Graphical Documents |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
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Volume |
8746 |
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25-37 |
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Graph representation of graphical documents often suffers from noise such as spurious nodes and edges, and their discontinuity. In general these errors occur during the low-level image processing viz. binarization, skeletonization, vectorization etc. Hierarchical graph representation is a nice and efficient way to solve this kind of problem by hierarchically merging node-node and node-edge depending on the distance. But the creation of hierarchical graph representing the graphical information often uses hard thresholds on the distance to create the hierarchical nodes (next state) of the lower nodes (or states) of a graph. As a result, the representation often loses useful information. This paper introduces plausibilities to the nodes of hierarchical graph as a function of distance and proposes a modified algorithm for matching subgraphs of the hierarchical graphs. The plausibility-annotated nodes help to improve the performance of the matching algorithm on two hierarchical structures. To show the potential of this approach, we conduct an experiment with the SESYD dataset. |
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Springer Berlin Heidelberg |
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Bart Lamiroy; Jean-Marc Ogier |
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LNCS |
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0302-9743 |
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978-3-662-44853-3 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.045; 600.056; 600.061; 600.077 |
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no |
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Admin @ si @ BDJ2014 |
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2699 |
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Author |
Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez;Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Perceptual retrieval of architectural floor plans |
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Conference Article |
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Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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This paper proposes a runlength histogram signature as a percetual descriptor of architectural plans in a retrieval scenario. The style of an architectural drawing is characterized by the perception of lines, shapes and texture. Such visual stimuli are the basis for defining semantic concepts as space properties, symmetry, density, etc. We propose runlength histograms extracted in vertical, horizontal and diagonal directions as a characterization of line and space properties in floorplans, so it can be roughly associated to a description of walls and room structure. A retrieval application illustrates the performance of the proposed approach, where given a plan as a query,
similar ones are obtained from a database. A ground truth based on human observation has been constructed to validate the hypothesis. Preliminary results show the interest of the proposed approach and opens a challenging research line in graphics recognition. |
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Bethlehem; PA; USA; August 2013 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.045; 600.056; 600.061 |
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no |
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Call Number |
Admin @ si @ HFF2013a |
Serial |
2320 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
Type |
Conference Article |
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Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. |
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Bethlehem; PA; USA; August 2013 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.045; 600.055; 600.061; 602.101 |
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no |
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Admin @ si @ RKL2013 |
Serial |
2347 |
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Author |
Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Spotting Graphical Symbols in Camera-Acquired Documents in Real Time |
Type |
Book Chapter |
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Year |
2014 |
Publication |
Graphics Recognition. Current Trends and Challenges |
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Volume |
8746 |
Issue |
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3-10 |
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In this paper we present a system devoted to spot graphical symbols in camera-acquired document images. The system is based on the extraction and further matching of ORB compact local features computed over interest key-points. Then, the FLANN indexing framework based on approximate nearest neighbor search allows to efficiently match local descriptors between the captured scene and the graphical models. Finally, the RANSAC algorithm is used in order to compute the homography between the spotted symbol and its appearance in the document image. The proposed approach is efficient and is able to work in real time. |
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Springer Berlin Heidelberg |
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Bart Lamiroy; Jean-Marc Ogier |
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0302-9743 |
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978-3-662-44853-3 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.045; 600.055; 600.061; 600.077 |
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no |
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Admin @ si @ RKL2014 |
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2700 |
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Permanent link to this record |
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Author |
Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Combining structural and statistical strategies for unsupervised wall detection in floor plans |
Type |
Conference Article |
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Year |
2013 |
Publication |
10th IAPR International Workshop on Graphics Recognition |
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This paper presents an evolution of the first unsupervised wall segmentation method in floor plans, that was presented by the authors in [1]. This first approach, contrarily to the existing ones, is able to segment walls independently to their notation and without the need of any pre-annotated data
to learn their visual appearance. Despite the good performance of the first approach, some specific cases, such as curved shaped walls, were not correctly segmented since they do not agree the strict structural assumptions that guide the whole methodology in order to be able to learn, in an unsupervised way, the structure of a wall. In this paper, we refine this strategy by dividing the
process in two steps. In a first step, potential wall segments are extracted unsupervisedly using a modification of [1], by restricting even more the areas considered as walls in a first moment. In a second step, these segments are used to learn and spot lost instances based on a modified version of [2], also presented by the authors. The presented combined method have been tested on
4 datasets with different notations and compared with the stateof-the-art applyed on the same datasets. The results show its adaptability to different wall notations and shapes, significantly outperforming the original approach. |
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Bethlehem; PA; USA; August 2013 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.045 |
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no |
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Admin @ si @ HVS2013a |
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2321 |
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Author |
Anjan Dutta; Josep Llados; Umapada Pal |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
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Title |
A symbol spotting approach in graphical documents by hashing serialized graphs |
Type |
Journal Article |
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Year |
2013 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
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Volume |
46 |
Issue |
3 |
Pages |
752-768 |
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Keywords |
Symbol spotting; Graphics recognition; Graph matching; Graph serialization; Graph factorization; Graph paths; Hashing |
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Abstract |
In this paper we propose a symbol spotting technique in graphical documents. Graphs are used to represent the documents and a (sub)graph matching technique is used to detect the symbols in them. We propose a graph serialization to reduce the usual computational complexity of graph matching. Serialization of graphs is performed by computing acyclic graph paths between each pair of connected nodes. Graph paths are one-dimensional structures of graphs which are less expensive in terms of computation. At the same time they enable robust localization even in the presence of noise and distortion. Indexing in large graph databases involves a computational burden as well. We propose a graph factorization approach to tackle this problem. Factorization is intended to create a unified indexed structure over the database of graphical documents. Once graph paths are extracted, the entire database of graphical documents is indexed in hash tables by locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. We have performed detailed experiments with various datasets of line drawings and compared our method with the state-of-the-art works. The results demonstrate the effectiveness and efficiency of our technique. |
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Elsevier |
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0031-3203 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.042; 600.045; 605.203; 601.152 |
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Admin @ si @ DLP2012 |
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2127 |
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Author |
Albert Gordo; Florent Perronnin; Ernest Valveny |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Large-scale document image retrieval and classification with runlength histograms and binary embeddings |
Type |
Journal Article |
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Year |
2013 |
Publication |
Pattern Recognition |
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PR |
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46 |
Issue |
7 |
Pages |
1898-1905 |
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visual document descriptor; compression; large-scale; retrieval; classification |
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We present a new document image descriptor based on multi-scale runlength
histograms. This descriptor does not rely on layout analysis and can be
computed efficiently. We show how this descriptor can achieve state-of-theart
results on two very different public datasets in classification and retrieval
tasks. Moreover, we show how we can compress and binarize these descriptors
to make them suitable for large-scale applications. We can achieve state-ofthe-
art results in classification using binary descriptors of as few as 16 to 64
bits. |
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Elsevier |
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0031-3203 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.042; 600.045; 605.203 |
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no |
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Admin @ si @ GPV2013 |
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2306 |
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Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard |
![goto web page url](img/www.gif)
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
Fuzzy Multilevel Graph Embedding |
Type |
Journal Article |
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Year |
2013 |
Publication |
Pattern Recognition |
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PR |
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Volume |
46 |
Issue |
2 |
Pages |
551-565 |
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Pattern recognition; Graphics recognition; Graph clustering; Graph classification; Explicit graph embedding; Fuzzy logic |
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Structural pattern recognition approaches offer the most expressive, convenient, powerful but computational expensive representations of underlying relational information. To benefit from mature, less expensive and efficient state-of-the-art machine learning models of statistical pattern recognition they must be mapped to a low-dimensional vector space. Our method of explicit graph embedding bridges the gap between structural and statistical pattern recognition. We extract the topological, structural and attribute information from a graph and encode numeric details by fuzzy histograms and symbolic details by crisp histograms. The histograms are concatenated to achieve a simple and straightforward embedding of graph into a low-dimensional numeric feature vector. Experimentation on standard public graph datasets shows that our method outperforms the state-of-the-art methods of graph embedding for richly attributed graphs. |
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Elsevier |
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0031-3203 |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 600.042; 600.045; 605.203 |
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Admin @ si @ LRL2013a |
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2270 |
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Author |
Emanuele Vivoli; Ali Furkan Biten; Andres Mafla; Dimosthenis Karatzas; Lluis Gomez |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
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Title |
MUST-VQA: MUltilingual Scene-text VQA |
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Conference Article |
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Year |
2022 |
Publication |
Proceedings European Conference on Computer Vision Workshops |
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13804 |
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345–358 |
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Visual question answering; Scene text; Translation robustness; Multilingual models; Zero-shot transfer; Power of language models |
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In this paper, we present a framework for Multilingual Scene Text Visual Question Answering that deals with new languages in a zero-shot fashion. Specifically, we consider the task of Scene Text Visual Question Answering (STVQA) in which the question can be asked in different languages and it is not necessarily aligned to the scene text language. Thus, we first introduce a natural step towards a more generalized version of STVQA: MUST-VQA. Accounting for this, we discuss two evaluation scenarios in the constrained setting, namely IID and zero-shot and we demonstrate that the models can perform on a par on a zero-shot setting. We further provide extensive experimentation and show the effectiveness of adapting multilingual language models into STVQA tasks. |
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Tel-Aviv; Israel; October 2022 |
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ECCVW |
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Notes ![sorted by Notes field, descending order (down)](img/sort_desc.gif) |
DAG; 302.105; 600.155; 611.002 |
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Admin @ si @ VBM2022 |
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3770 |
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Author |
Agnes Borras; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Object Image Retrieval by Shape Content in Complex Scenes Using Geometric Constraints |
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Book Chapter |
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Year |
2005 |
Publication |
Pattern Recognition And Image Analysis |
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LNCS |
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3522 |
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325–332 |
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This paper presents an image retrieval system based on 2D shape information. Query shape objects and database images are repre- sented by polygonal approximations of their contours. Afterwards they are encoded, using geometric features, in terms of predefined structures. Shapes are then located in database images by a voting procedure on the spatial domain. Then an alignment matching provides a probability value to rank de database image in the retrieval result. The method al- lows to detect a query object in database images even when they contain complex scenes. Also the shape matching tolerates partial occlusions and affine transformations as translation, rotation or scaling. |
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Estoril (Portugal) |
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Springer Link |
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DAG @ dag @ BoL2005; IAM @ iam @ BoL2005 |
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556 |
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Author |
Agnes Borras; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Similarity-Based Object Retrieval Using Appearance and Geometric Feature Combination |
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Book Chapter |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:113–120 |
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4478 |
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33–39 |
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This work presents a content-based image retrieval system of general purpose that deals with cluttered scenes containing a given query object. The system is flexible enough to handle with a single image of an object despite its rotation, translation and scale variations. The image content is divided in parts that are described with a combination of features based on geometrical and color properties. The idea behind the feature combination is to benefit from a fuzzy similarity computation that provides robustness and tolerance to the retrieval process. The features can be independently computed and the image parts can be easily indexed by using a table structure on every feature value. Finally a process inspired in the alignment strategies is used to check the coherence of the object parts found in a scene. Our work presents a system of easy implementation that uses an open set of features and can suit a wide variety of applications. |
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Girona (Spain) |
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978-3-540-72848-1 |
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DAG @ dag @ BoL2007a; IAM @ iam @ BoL2007a |
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776 |
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Author |
Agnes Borras |
![download PDF file pdf](img/file_PDF.gif)
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Contributions to the Content-Based Image Retrieval Using Pictorial Queries |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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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Barcelona (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Bellaterra |
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Josep Llados |
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DAG @ dag @ Bor2009; IAM @ iam @ Bor2009 |
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1269 |
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Author |
Jon Almazan; Ernest Valveny; Alicia Fornes |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
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Conference Article |
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2011 |
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5th Iberian Conference on Pattern Recognition and Image Analysis |
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6669 |
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1-8 |
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This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance. |
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Las Palmas de Gran Canaria. Spain |
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Springer-Verlag |
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Berlin |
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Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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IbPRIA |
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Admin @ si @ AVF2011 |
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1732 |
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