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| Author | Lluis Pere de las Heras; Ernest Valveny; Gemma Sanchez | ||||
| Title | Combining structural and statistical strategies for unsupervised wall detection in floor plans | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
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| Abstract | 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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| Address | Bethlehem; PA; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | GREC | ||
Notes  |
DAG; 600.045 | Approved | no | ||
| Call Number | Admin @ si @ HVS2013a | Serial | 2321 | ||
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| Author | Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados | ||||
| Title | Spotting Graphical Symbols in Camera-Acquired Documents in Real Time | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
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| Abstract | 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. | ||||
| Address | Bethlehem; PA; USA; August 2013 | ||||
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| 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; 600.045; 600.055; 600.061; 602.101 | Approved | no | ||
| Call Number | Admin @ si @ RKL2013 | Serial | 2347 | ||
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| Author | Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez;Josep Llados | ||||
| Title | Perceptual retrieval of architectural floor plans | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
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| Abstract | 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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| Address | Bethlehem; PA; USA; August 2013 | ||||
| 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; 600.045; 600.056; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ HFF2013a | Serial | 2320 | ||
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| Author | Klaus Broelemann; Anjan Dutta; Xiaoyi Jiang; Josep Llados | ||||
| Title | Plausibility-Graphs for Symbol Spotting in Graphical Documents | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
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| Abstract | 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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| Address | Bethlehem; PA; USA; August 2013 | ||||
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| 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; 600.045; 600.056; 600.061; 601.152 | Approved | no | ||
| Call Number | Admin @ si @ BDJ2013 | Serial | 2360 | ||
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| Author | Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal | ||||
| Title | Near Convex Region Adjacency Graph and Approximate Neighborhood String Matching for Symbol Spotting in Graphical Documents | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1078-1082 | ||
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| Abstract | 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. | ||||
| Address | Washington; USA; August 2013 | ||||
| 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 | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG; 600.045; 600.056; 600.061; 601.152 | Approved | no | ||
| Call Number | Admin @ si @ DLB2013a | Serial | 2358 | ||
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| Author | Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny | ||||
| Title | Notation-invariant patch-based wall detector in architectural floor plans | Type | Book Chapter | ||
| Year | 2013 | Publication | Graphics Recognition. New Trends and Challenges | Abbreviated Journal | |
| Volume | 7423 | Issue | Pages | 79--88 | |
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| Abstract | Architectural floor plans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed in [1], showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. This paper presents an evolution of that previous work, after analyzing and testing several alternatives for each of the different steps of the method: Firstly, an automatic plan-size normalization process is done. Secondly we evaluate different features to obtain the description of every patch. Thirdly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These variations of the method have been tested for wall detection on two datasets of architectural floor plans with different notations. After studying in deep each of the steps in the process pipeline, we are able to find the best system configuration, which highly outperforms the results on wall segmentation obtained by the original paper. | ||||
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| Corporate Author | Thesis | ||||
| Publisher | Springer Berlin 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 | 978-3-642-36823-3 | Medium | |
| Area | Expedition | Conference | |||
| Notes |
DAG; 600.045; 600.056; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ HMS2013 | Serial | 2322 | ||
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| Author | V.C.Kieu; Alicia Fornes; M. Visani; N.Journet ; Anjan Dutta | ||||
| Title | The ICDAR/GREC 2013 Music Scores Competition on Staff Removal | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | Competition; Music scores; Staff Removal | ||||
| Abstract | The first competition on music scores that was organized at ICDAR and GREC in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we propose a staff removal competition where we simulate old music scores. Thus, we have created a new set of images, which contain noise and 3D distortions. This paper describes the distortion methods, metrics, the participant’s methods and the obtained results. | ||||
| Address | Bethlehem; PA; USA; August 2013 | ||||
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| 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; 600.045; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ KFV2013 | Serial | 2337 | ||
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| Author | M. Visani; V.C.Kieu; Alicia Fornes; N.Journet | ||||
| Title | The ICDAR 2013 Music Scores Competition: Staff Removal | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1439-1443 | ||
| Keywords | |||||
| Abstract | The first competition on music scores that was organized at ICDAR in 2011 awoke the interest of researchers, who participated both at staff removal and writer identification tasks. In this second edition, we focus on the staff removal task and simulate a real case scenario: old music scores. For this purpose, we have generated a new set of images using two kinds of degradations: local noise and 3D distortions. This paper describes the dataset, distortion methods, evaluation metrics, the participant's methods and the obtained results. | ||||
| Address | Washington; USA; August 2013 | ||||
| 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 | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG; 600.045; 600.061 | Approved | no | ||
| Call Number | Admin @ si @ VKF2013 | Serial | 2338 | ||
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| Author | Lluis Pere de las Heras; David Fernandez; Alicia Fornes; Ernest Valveny; Gemma Sanchez; Josep Llados | ||||
| Title | Runlength Histogram Image Signature for Perceptual Retrieval of Architectural Floor Plans | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | |||
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| Abstract | |||||
| Address | Bethlehem; PA; USA; August 2013 | ||||
| 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; 600.045; 600.061; 600.056 | Approved | no | ||
| Call Number | Admin @ si @ HFF2013b | Serial | 2695 | ||
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| Author | Veronica Romero; Alicia Fornes; Nicolas Serrano; Joan Andreu Sanchez; A.H. Toselli; Volkmar Frinken; E. Vidal; Josep Llados | ||||
| Title | The ESPOSALLES database: An ancient marriage license corpus for off-line handwriting recognition | Type | Journal Article | ||
| Year | 2013 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 46 | Issue | 6 | Pages | 1658-1669 |
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| Abstract | Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demography studies and genealogical research. Automatic processing of historical documents, however, has mostly been focused on single works of literature and less on social records, which tend to have a distinct layout, structure, and vocabulary. Such information is usually collected by expert demographers that devote a lot of time to manually transcribe them. This paper presents a new database, compiled from a marriage license books collection, to support research in automatic handwriting recognition for historical documents containing social records. Marriage license books are documents that were used for centuries by ecclesiastical institutions to register marriage licenses. Books from this collection are handwritten and span nearly half a millennium until the beginning of the 20th century. In addition, a study is presented about the capability of state-of-the-art handwritten text recognition systems, when applied to the presented database. Baseline results are reported for reference in future studies. | ||||
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| Publisher | Elsevier Science Inc. New York, NY, USA | Place of Publication | Editor | ||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0031-3203 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes |
DAG; 600.045; 602.006; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ RFS2013 | Serial | 2298 | ||
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| Author | Andreas Fischer; Ching Y. Suen; Volkmar Frinken; Kaspar Riesen; Horst Bunke | ||||
| Title | A Fast Matching Algorithm for Graph-Based Handwriting Recognition | Type | Conference Article | ||
| Year | 2013 | Publication | 9th IAPR – TC15 Workshop on Graph-based Representation in Pattern Recognition | Abbreviated Journal | |
| Volume | 7877 | Issue | Pages | 194-203 | |
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| Abstract | The recognition of unconstrained handwriting images is usually based on vectorial representation and statistical classification. Despite their high representational power, graphs are rarely used in this field due to a lack of efficient graph-based recognition methods. Recently, graph similarity features have been proposed to bridge the gap between structural representation and statistical classification by means of vector space embedding. This approach has shown a high performance in terms of accuracy but had shortcomings in terms of computational speed. The time complexity of the Hungarian algorithm that is used to approximate the edit distance between two handwriting graphs is demanding for a real-world scenario. In this paper, we propose a faster graph matching algorithm which is derived from the Hausdorff distance. On the historical Parzival database it is demonstrated that the proposed method achieves a speedup factor of 12.9 without significant loss in recognition accuracy. | ||||
| Address | Vienna; Austria; May 2013 | ||||
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| Publisher | Springer Berlin 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 | 978-3-642-38220-8 | Medium | |
| Area | Expedition | Conference | GBR | ||
| Notes |
DAG; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ FSF2013 | Serial | 2294 | ||
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| Author | Andreas Fischer; Volkmar Frinken; Horst Bunke; Ching Y. Suen | ||||
| Title | Improving HMM-Based Keyword Spotting with Character Language Models | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 506-510 | ||
| Keywords | |||||
| Abstract | Facing high error rates and slow recognition speed for full text transcription of unconstrained handwriting images, keyword spotting is a promising alternative to locate specific search terms within scanned document images. We have previously proposed a learning-based method for keyword spotting using character hidden Markov models that showed a high performance when compared with traditional template image matching. In the lexicon-free approach pursued, only the text appearance was taken into account for recognition. In this paper, we integrate character n-gram language models into the spotting system in order to provide an additional language context. On the modern IAM database as well as the historical George Washington database, we demonstrate that character language models significantly improve the spotting performance. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG; 600.045; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ FFB2013 | Serial | 2295 | ||
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| Author | Dimosthenis Karatzas; Faisal Shafait; Seiichi Uchida; Masakazu Iwamura; Lluis Gomez; Sergi Robles; Joan Mas; David Fernandez; Jon Almazan; Lluis Pere de las Heras | ||||
| Title | ICDAR 2013 Robust Reading Competition | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 1484-1493 | ||
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| Abstract | This report presents the final results of the ICDAR 2013 Robust Reading Competition. The competition is structured in three Challenges addressing text extraction in different application domains, namely born-digital images, real scene images and real-scene videos. The Challenges are organised around specific tasks covering text localisation, text segmentation and word recognition. The competition took place in the first quarter of 2013, and received a total of 42 submissions over the different tasks offered. This report describes the datasets and ground truth specification, details the performance evaluation protocols used and presents the final results along with a brief summary of the participating methods. | ||||
| Address | Washington; USA; August 2013 | ||||
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | Original Title | |||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG; 600.056 | Approved | no | ||
| Call Number | Admin @ si @ KSU2013 | Serial | 2318 | ||
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| Author | Christophe Rigaud; Dimosthenis Karatzas; Jean-Christophe Burie; Jean-Marc Ogier | ||||
| Title | Speech balloon contour classification in comics | Type | Conference Article | ||
| Year | 2013 | Publication | 10th IAPR International Workshop on Graphics Recognition | Abbreviated Journal | |
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| Abstract | Comic books digitization combined with subsequent comic book understanding create a variety of new applications, including mobile reading and data mining. Document understanding in this domain is challenging as comics are semi-structured documents, combining semantically important graphical and textual parts. In this work we detail a novel approach for classifying speech balloon in scanned comics book pages based on their contour time series. | ||||
| Address | Bethlehem; PA; USA; August 2013 | ||||
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| Language | Summary Language | Original Title | |||
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| ISSN | ISBN | Medium | |||
| Area | Expedition | Conference | GREC | ||
| Notes |
DAG; 600.056 | Approved | no | ||
| Call Number | Admin @ si @ RKB2013 | Serial | 2429 | ||
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| Author | Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados; Tomokazu Sato; Masakazu Iwamura; Koichi Kise | ||||
| Title | Key-region detection for document images -applications to administrative document retrieval | Type | Conference Article | ||
| Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
| Volume | Issue | Pages | 230-234 | ||
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| Abstract | In this paper we argue that a key-region detector designed to take into account the special characteristics of document images can result in the detection of less and more meaningful key-regions. We propose a fast key-region detector able to capture aspects of the structural information of the document, and demonstrate its efficiency by comparing against standard detectors in an administrative document retrieval scenario. We show that using the proposed detector results to a smaller number of detected key-regions and higher performance without any drop in speed compared to standard state of the art detectors. | ||||
| Address | Washington; USA; August 2013 | ||||
| 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 | 1520-5363 | ISBN | Medium | ||
| Area | Expedition | Conference | ICDAR | ||
| Notes |
DAG; 600.056; 600.045 | Approved | no | ||
| Call Number | Admin @ si @ GRK2013b | Serial | 2293 | ||
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