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Author |
Sanket Biswas; Pau Riba; Josep Llados; Umapada Pal |
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Title  |
Graph-Based Deep Generative Modelling for Document Layout Generation |
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Conference Article |
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Year |
2021 |
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16th International Conference on Document Analysis and Recognition |
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12917 |
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525-537 |
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Abstract |
One of the major prerequisites for any deep learning approach is the availability of large-scale training data. When dealing with scanned document images in real world scenarios, the principal information of its content is stored in the layout itself. In this work, we have proposed an automated deep generative model using Graph Neural Networks (GNNs) to generate synthetic data with highly variable and plausible document layouts that can be used to train document interpretation systems, in this case, specially in digital mailroom applications. It is also the first graph-based approach for document layout generation task experimented on administrative document images, in this case, invoices. |
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Lausanne; Suissa; September 2021 |
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DAG; 600.121; 600.140; 110.312 |
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Admin @ si @ BRL2021 |
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3676 |
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Author |
Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes |
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Title |
Graph-based deep learning for graphics classification |
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Conference Article |
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Year |
2017 |
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12th IAPR International Workshop on Graphics Recognition |
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29-30 |
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Graph-based representations are a common way to deal with graphics recognition problems. However, previous works were mainly focused on developing learning-free techniques. The success of deep learning frameworks have proved that learning is a powerful tool to solve many problems, however it is not straightforward to extend these methodologies to non euclidean data such as graphs. On the other hand, graphs are a good representational structure for graphical entities. In this work, we present some deep learning techniques that have been proposed in the literature for graph-based representations and
we show how they can be used in graphics recognition problems |
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GREC |
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DAG; 600.097; 601.302; 600.121 |
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Admin @ si @ RDL2017b |
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3058 |
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Author |
Miquel Ferrer; Ernest Valveny; F. Serratosa; I. Bardaji; Horst Bunke |
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Title |
Graph-based k-means clustering: A comparison of the set versus the generalized median graph |
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Conference Article |
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2009 |
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13th International Conference on Computer Analysis of Images and Patterns |
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5702 |
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342–350 |
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In this paper we propose the application of the generalized median graph in a graph-based k-means clustering algorithm. In the graph-based k-means algorithm, the centers of the clusters have been traditionally represented using the set median graph. We propose an approximate method for the generalized median graph computation that allows to use it to represent the centers of the clusters. Experiments on three databases show that using the generalized median graph as the clusters representative yields better results than the set median graph. |
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Münster, Germany |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-03766-5 |
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CAIP |
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DAG |
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DAG @ dag @ FVS2009d |
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1219 |
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Author |
Aura Hernandez-Sabate; Lluis Albarracin; F. Javier Sanchez |
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Title |
Graph-Based Problem Explorer: A Software Tool to Support Algorithm Design Learning While Solving the Salesperson Problem |
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Journal |
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2020 |
Publication |
Mathematics |
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MATH |
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20 |
Issue |
8(9) |
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1595 |
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STEM education; Project-based learning; Coding; software tool |
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In this article, we present a sequence of activities in the form of a project in order to promote
learning on design and analysis of algorithms. The project is based on the resolution of a real problem, the salesperson problem, and it is theoretically grounded on the fundamentals of mathematical modelling. In order to support the students’ work, a multimedia tool, called Graph-based Problem Explorer (GbPExplorer), has been designed and refined to promote the development of computer literacy in engineering and science university students. This tool incorporates several modules to allow coding different algorithmic techniques solving the salesman problem. Based on an educational design research along five years, we observe that working with GbPExplorer during the project provides students with the possibility of representing the situation to be studied in the form of graphs and analyze them from a computational point of view. |
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September 2020 |
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IAM; ISE |
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Admin @ si @ |
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3722 |
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Author |
Josep Llados; Enric Marti |
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Title |
Graph-edit algorithms for hand-drawn graphical document recognition and their automatic introduction |
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Journal Article |
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1999 |
Publication |
Machine Graphics & Vision journal, special issue on Graph transformation |
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DAG;IAM |
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IAM @ iam @ LIM1999c |
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1569 |
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Author |
Josep Llados; Marçal Rusiñol |
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Title |
Graphics Recognition Techniques |
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Book Chapter |
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2014 |
Publication |
Handbook of Document Image Processing and Recognition |
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D |
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489-521 |
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Dimension recognition; Graphics recognition; Graphic-rich documents; Polygonal approximation; Raster-to-vector conversion; Texture-based primitive extraction; Text-graphics separation |
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Abstract |
This chapter describes the most relevant approaches for the analysis of graphical documents. The graphics recognition pipeline can be splitted into three tasks. The low level or lexical task extracts the basic units composing the document. The syntactic level is focused on the structure, i.e., how graphical entities are constructed, and involves the location and classification of the symbols present in the document. The third level is a functional or semantic level, i.e., it models what the graphical symbols do and what they mean in the context where they appear. This chapter covers the lexical level, while the next two chapters are devoted to the syntactic and semantic level, respectively. The main problems reviewed in this chapter are raster-to-vector conversion (vectorization algorithms) and the separation of text and graphics components. The research and industrial communities have provided standard methods achieving reasonable performance levels. Hence, graphics recognition techniques can be considered to be in a mature state from a scientific point of view. Additionally this chapter provides insights on some related problems, namely, the extraction and recognition of dimensions in engineering drawings, and the recognition of hatched and tiled patterns. Both problems are usually associated, even integrated, in the vectorization process. |
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Springer London |
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D. Doermann; K. Tombre |
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978-0-85729-858-4 |
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DAG; 600.077 |
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Admin @ si @ LlR2014 |
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2380 |
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Author |
Alicia Fornes; Bart Lamiroy |
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Title |
Graphics Recognition, Current Trends and Evolutions |
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2018 |
Publication |
Graphics Recognition, Current Trends and Evolutions |
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11009 |
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This book constitutes the thoroughly refereed post-conference proceedings of the 12th International Workshop on Graphics Recognition, GREC 2017, held in Kyoto, Japan, in November 2017.
The 10 revised full papers presented were carefully reviewed and selected from 14 initial submissions. They contain both classical and emerging topics of graphics rcognition, namely analysis and detection of diagrams, search and classification, optical music recognition, interpretation of engineering drawings and maps. |
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Springer International Publishing |
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978-3-030-02283-9 |
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DAG; 600.121 |
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Admin @ si @ FoL2018 |
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3171 |
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Author |
Liu Wenyin; Josep Llados; Jean-Marc Ogier |
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Title |
Graphics Recognition. Recent Advances and New Opportunities. |
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Book Whole |
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2008 |
Publication |
7th International Workshop, Selected Papers, |
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5046 |
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Curitiba (Brazil) |
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978-3-540-88184-1 |
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DAG |
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DAG @ dag @ WLO2008 |
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1012 |
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Author |
Josep Llados; Young-Bin Kwon |
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Graphics Recognition. Recent Advances and Perspectives |
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2004 |
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LNCS 3080, ISBN: 3–540–22478–5 |
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Springer-Verlag |
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DAG @ dag @ LlK2004 |
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515 |
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Author |
W. Liu; Josep Llados |
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Graphics Recognition. Ten Years Review and Future Perspectives |
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2006 |
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6th International Workshop |
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3926 |
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Hong Kong (China) |
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DAG |
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DAG @ dag @ LiL2006 |
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800 |
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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 |
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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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DAG |
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Admin @ si @ OLL2010 |
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1976 |
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Author |
Ayan Banerjee; Sanket Biswas; Josep Llados; Umapada Pal |
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Title |
GraphKD: Exploring Knowledge Distillation Towards Document Object Detection with Structured Graph Creation |
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Miscellaneous |
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2024 |
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Arxiv |
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Object detection in documents is a key step to automate the structural elements identification process in a digital or scanned document through understanding the hierarchical structure and relationships between different elements. Large and complex models, while achieving high accuracy, can be computationally expensive and memory-intensive, making them impractical for deployment on resource constrained devices. Knowledge distillation allows us to create small and more efficient models that retain much of the performance of their larger counterparts. Here we present a graph-based knowledge distillation framework to correctly identify and localize the document objects in a document image. Here, we design a structured graph with nodes containing proposal-level features and edges representing the relationship between the different proposal regions. Also, to reduce text bias an adaptive node sampling strategy is designed to prune the weight distribution and put more weightage on non-text nodes. We encode the complete graph as a knowledge representation and transfer it from the teacher to the student through the proposed distillation loss by effectively capturing both local and global information concurrently. Extensive experimentation on competitive benchmarks demonstrates that the proposed framework outperforms the current state-of-the-art approaches. The code will be available at: this https URL. |
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Admin @ si @ BBL2024b |
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4023 |
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Author |
Ricard Coll; Alicia Fornes; Josep Llados |
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Title |
Graphological Analysis of Handwritten Text Documents for Human Resources Recruitment |
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Conference Article |
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2009 |
Publication |
10th International Conference on Document Analysis and Recognition |
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1081–1085 |
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The use of graphology in recruitment processes has become a popular tool in many human resources companies. This paper presents a model that links features from handwritten images to a number of personality characteristics used to measure applicant aptitudes for the job in a particular hiring scenario. In particular we propose a model of measuring active personality and leadership of the writer. Graphological features that define such a profile are measured in terms of document and script attributes like layout configuration, letter size, shape, slant and skew angle of lines, etc. After the extraction, data is classified using a neural network. An experimental framework with real samples has been constructed to illustrate the performance of the approach. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG |
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DAG @ dag @ CFL2009 |
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1221 |
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Author |
Joan M. Nuñez; Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Growing Algorithm for Intersection Detection (GRAID) in branching patterns |
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Journal Article |
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2015 |
Publication |
Machine Vision and Applications |
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MVAP |
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26 |
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2 |
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387-400 |
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Bifurcation ; Crossroad; Intersection ;Retina ; Vessel |
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Analysis of branching structures represents a very important task in fields such as medical diagnosis, road detection or biometrics. Detecting intersection landmarks Becomes crucial when capturing the structure of a branching pattern. We present a very simple geometrical model to describe intersections in branching structures based on two conditions: Bounded Tangency condition (BT) and Shortest Branch (SB) condition. The proposed model precisely sets a geometrical characterization of intersections and allows us to introduce a new unsupervised operator for intersection extraction. We propose an implementation that handles the consequences of digital domain operation that,unlike existing approaches, is not restricted to a particular scale and does not require the computation of the thinned pattern. The new proposal, as well as other existing approaches in the bibliography, are evaluated in a common framework for the first time. The performance analysis is based on two manually segmented image data sets: DRIVE retinal image database and COLON-VESSEL data set, a newly created data set of vascular content in colonoscopy frames. We have created an intersection landmark ground truth for each data set besides comparing our method in the only existing ground truth. Quantitative results confirm that we are able to outperform state-of-the-art performancelevels with the advantage that neither training nor parameter tuning is needed. |
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;SIAI |
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no |
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Admin @ si @MBS2015 |
Serial |
2777 |
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Author |
Jorge Bernal; Aymeric Histace; Marc Masana; Quentin Angermann; Cristina Sanchez Montes; Cristina Rodriguez de Miguel; Maroua Hammami; Ana Garcia Rodriguez; Henry Cordova; Olivier Romain; Gloria Fernandez Esparrach; Xavier Dray; F. Javier Sanchez |
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Title |
GTCreator: a flexible annotation tool for image-based datasets |
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Journal Article |
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Year |
2019 |
Publication |
International Journal of Computer Assisted Radiology and Surgery |
Abbreviated Journal |
IJCAR |
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Volume |
14 |
Issue |
2 |
Pages |
191–201 |
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Keywords |
Annotation tool; Validation Framework; Benchmark; Colonoscopy; Evaluation |
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Abstract |
Abstract Purpose: Methodology evaluation for decision support systems for health is a time consuming-task. To assess performance of polyp detection
methods in colonoscopy videos, clinicians have to deal with the annotation
of thousands of images. Current existing tools could be improved in terms of
exibility and ease of use. Methods:We introduce GTCreator, a exible annotation tool for providing image and text annotations to image-based datasets.
It keeps the main basic functionalities of other similar tools while extending
other capabilities such as allowing multiple annotators to work simultaneously
on the same task or enhanced dataset browsing and easy annotation transfer aiming to speed up annotation processes in large datasets. Results: The
comparison with other similar tools shows that GTCreator allows to obtain
fast and precise annotation of image datasets, being the only one which offers
full annotation editing and browsing capabilites. Conclusions: Our proposed
annotation tool has been proven to be efficient for large image dataset annota-
tion, as well as showing potential of use in other stages of method evaluation
such as experimental setup or results analysis. |
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Notes |
MV; 600.096; 600.109; 600.119; 601.305 |
Approved |
no |
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Call Number |
Admin @ si @ BHM2019 |
Serial |
3163 |
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