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Author (up) David Fernandez; Josep Llados; Alicia Fornes edit  doi
openurl 
  Title A graph-based approach for segmenting touching lines in historical handwritten documents Type Journal Article
  Year 2014 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 17 Issue 3 Pages 293-312  
  Keywords Text line segmentation; Handwritten documents; Document image processing; Historical document analysis  
  Abstract Text line segmentation in handwritten documents is an important task in the recognition of historical documents. Handwritten document images contain text lines with multiple orientations, touching and overlapping characters between consecutive text lines and different document structures, making line segmentation a difficult task. In this paper, we present a new approach for handwritten text line segmentation solving the problems of touching components, curvilinear text lines and horizontally overlapping components. The proposed algorithm formulates line segmentation as finding the central path in the area between two consecutive lines. This is solved as a graph traversal problem. A graph is constructed using the skeleton of the image. Then, a path-finding algorithm is used to find the optimum path between text lines. The proposed algorithm has been evaluated on a comprehensive dataset consisting of five databases: ICDAR2009, ICDAR2013, UMD, the George Washington and the Barcelona Marriages Database. The proposed method outperforms the state-of-the-art considering the different types and difficulties of the benchmarking data.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.056; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ FLF2014 Serial 2459  
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Author (up) David Fernandez; Josep Llados; Alicia Fornes; R.Manmatha edit   pdf
doi  isbn
openurl 
  Title On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts Type Conference Article
  Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal  
  Volume Issue Pages 763-768  
  Keywords document image processing;handwritten character recognition;history;image segmentation;Spanish document;historical document;line segmentation;old handwritten document;old manuscript;word segmentation;Bifurcation;Dynamic programming;Handwriting recognition;Image segmentation;Measurement;Noise;Skeleton;Segmentation;document analysis;document and text processing;handwriting analysis;heuristics;path-finding  
  Abstract he objective of this work is to show the importance of a good line segmentation to obtain better results in the segmentation of words of historical documents. We have used the approach developed by Manmatha and Rothfeder [1] to segment words in old handwritten documents. In their work the lines of the documents are extracted using projections. In this work, we have developed an approach to segment lines more efficiently. The new line segmentation algorithm tackles with skewed, touching and noisy lines, so it is significantly improves word segmentation. Experiments using Spanish documents from the Marriages Database of the Barcelona Cathedral show that this approach reduces the error rate by more than 20%  
  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 ISBN 978-1-4673-2262-1 Medium  
  Area Expedition Conference ICFHR  
  Notes DAG Approved no  
  Call Number Admin @ si @ FLF2012 Serial 2200  
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Author (up) David Fernandez; Pau Riba; Alicia Fornes; Josep Llados edit   pdf
doi  isbn
openurl 
  Title On the Influence of Key Point Encoding for Handwritten Word Spotting Type Conference Article
  Year 2014 Publication 14th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal  
  Volume Issue Pages 476 - 481  
  Keywords Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis  
  Abstract In this paper we evaluate the influence of the selection of key points and the associated features in the performance of word spotting processes. In general, features can be extracted from a number of characteristic points like corners, contours, skeletons, maxima, minima, crossings, etc. A number of descriptors exist in the literature using different interest point detectors. But the intrinsic variability of handwriting vary strongly on the performance if the interest points are not stable enough. In this paper, we analyze the performance of different descriptors for local interest points. As benchmarking dataset we have used the Barcelona Marriage Database that contains handwritten records of marriages over five centuries.  
  Address Creete Island; Grecia; September 2014  
  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 2167-6445 ISBN 978-1-4799-4335-7 Medium  
  Area Expedition Conference ICFHR  
  Notes DAG; 600.056; 600.061; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ FRF2014 Serial 2460  
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Author (up) David Fernandez; R.Manmatha; Josep Llados; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title Sequential Word Spotting in Historical Handwritten Documents Type Conference Article
  Year 2014 Publication 11th IAPR International Workshop on Document Analysis and Systems Abbreviated Journal  
  Volume Issue Pages 101 - 105  
  Keywords  
  Abstract In this work we present a handwritten word spotting approach that takes advantage of the a priori known order of appearance of the query words. Given an ordered sequence of query word instances, the proposed approach performs a
sequence alignment with the words in the target collection. Although the alignment is quite sparse, i.e. the number of words in the database is higher than the query set, the improvement in the overall performance is sensitively higher than isolated word spotting. As application dataset, we use a collection of handwritten marriage licenses taking advantage of the ordered
index pages of family names.
 
  Address Tours; Francia; April 2014  
  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 978-1-4799-3243-6 Medium  
  Area Expedition Conference DAS  
  Notes DAG; 600.061; 600.056; 602.006; 600.077 Approved no  
  Call Number Admin @ si @ FML2014 Serial 2462  
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Author (up) David Fernandez; Simone Marinai; Josep Llados; Alicia Fornes edit   pdf
doi  isbn
openurl 
  Title Contextual Word Spotting in Historical Manuscripts using Markov Logic Networks Type Conference Article
  Year 2013 Publication 2nd International Workshop on Historical Document Imaging and Processing Abbreviated Journal  
  Volume Issue Pages 36-43  
  Keywords  
  Abstract Natural languages can often be modelled by suitable grammars whose knowledge can improve the word spotting results. The implicit contextual information is even more useful when dealing with information that is intrinsically described as one collection of records. In this paper, we present one approach to word spotting which uses the contextual information of records to improve the results. The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records. The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information.  
  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 ISBN 978-1-4503-2115-0 Medium  
  Area Expedition Conference HIP  
  Notes DAG; 600.056; 600.045; 600.061; 602.006 Approved no  
  Call Number Admin @ si @ FML2013 Serial 2308  
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Author (up) Debora Gil; Jordi Gonzalez; Gemma Sanchez (eds) edit  isbn
openurl 
  Title Computer Vision: Advances in Research and Development Type Book Whole
  Year 2007 Publication Proceedings of the 2nd CVC International Workshop Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher UAB Place of Publication Bellaterra (Spain) Editor Debora Gil; Jordi Gonzalez; Gemma Sanchez  
  Language Summary Language Original Title  
  Series Editor Series Title 2 Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-935251-4-9 Medium  
  Area Expedition Conference  
  Notes IAM; ISE; DAG Approved no  
  Call Number IAM @ iam @ GGS2007 Serial 1493  
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Author (up) Debora Gil; Oriol Ramos Terrades; Elisa Minchole; Carles Sanchez; Noelia Cubero de Frutos; Marta Diez-Ferrer; Rosa Maria Ortiz; Antoni Rosell edit   pdf
url  openurl
  Title Classification of Confocal Endomicroscopy Patterns for Diagnosis of Lung Cancer Type Conference Article
  Year 2017 Publication 6th Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging Abbreviated Journal  
  Volume 10550 Issue Pages 151-159  
  Keywords  
  Abstract Confocal Laser Endomicroscopy (CLE) is an emerging imaging technique that allows the in-vivo acquisition of cell patterns of potentially malignant lesions. Such patterns could discriminate between inflammatory and neoplastic lesions and, thus, serve as a first in-vivo biopsy to discard cases that do not actually require a cell biopsy.

The goal of this work is to explore whether CLE images obtained during videobronchoscopy contain enough visual information to discriminate between benign and malign peripheral lesions for lung cancer diagnosis. To do so, we have performed a pilot comparative study with 12 patients (6 adenocarcinoma and 6 benign-inflammatory) using 2 different methods for CLE pattern analysis: visual analysis by 3 experts and a novel methodology that uses graph methods to find patterns in pre-trained feature spaces. Our preliminary results indicate that although visual analysis can only achieve a 60.2% of accuracy, the accuracy of the proposed unsupervised image pattern classification raises to 84.6%.

We conclude that CLE images visual information allow in-vivo detection of neoplastic lesions and graph structural analysis applied to deep-learning feature spaces can achieve competitive results.
 
  Address Quebec; Canada; September 2017  
  Corporate Author Thesis  
  Publisher 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 CLIP  
  Notes IAM; 600.096; 600.075; 600.145;DAG Approved no  
  Call Number Admin @ si @ GRM2017 Serial 2957  
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Author (up) Debora Gil; Oriol Ramos Terrades; Raquel Perez edit   pdf
openurl 
  Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Conference Article
  Year 2020 Publication Women in Geometry and Topology Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Barcelona; September 2019  
  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  
  Notes IAM; DAG; 600.139; 600.145; 600.121 Approved no  
  Call Number Admin @ si @ GRP2020 Serial 3473  
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Author (up) Debora Gil; Oriol Ramos Terrades; Raquel Perez edit  doi
openurl 
  Title Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution Type Book Chapter
  Year 2021 Publication Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15 Abbreviated Journal  
  Volume 15 Issue Pages 89–93  
  Keywords  
  Abstract Abnormalities in radiomic measures correlate to genomic alterations prone to alter the outcome of personalized anti-cancer treatments. TOPiomics is a new method for the early detection of variations in tumor imaging phenotype from a topological structure in multi-view radiomic spaces.  
  Address  
  Corporate Author Thesis  
  Publisher Springer Nature 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  
  Notes IAM; DAG; 600.120; 600.145; 600.139 Approved no  
  Call Number Admin @ si @ GRP2021 Serial 3594  
Permanent link to this record
 

 
Author (up) Dena Bazazian edit  isbn
openurl 
  Title Fully Convolutional Networks for Text Understanding in Scene Images Type Book Whole
  Year 2018 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Text understanding in scene images has gained plenty of attention in the computer vision community and it is an important task in many applications as text carries semantically rich information about scene content and context. For instance, reading text in a scene can be applied to autonomous driving, scene understanding or assisting visually impaired people. The general aim of scene text understanding is to localize and recognize text in scene images. Text regions are first localized in the original image by a trained detector model and afterwards fed into a recognition module. The tasks of localization and recognition are highly correlated since an inaccurate localization can affect the recognition task.
The main purpose of this thesis is to devise efficient methods for scene text understanding. We investigate how the latest results on deep learning can advance text understanding pipelines. Recently, Fully Convolutional Networks (FCNs) and derived methods have achieved a significant performance on semantic segmentation and pixel level classification tasks. Therefore, we took benefit of the strengths of FCN approaches in order to detect text in natural scenes. In this thesis we have focused on two challenging tasks of scene text understanding which are Text Detection and Word Spotting. For the task of text detection, we have proposed an efficient text proposal technique in scene images. We have considered the Text Proposals method as the baseline which is an approach to reduce the search space of possible text regions in an image. In order to improve the Text Proposals method we combined it with Fully Convolutional Networks to efficiently reduce the number of proposals while maintaining the same level of accuracy and thus gaining a significant speed up. Our experiments demonstrate that this text proposal approach yields significantly higher recall rates than the line based text localization techniques, while also producing better-quality localization. We have also applied this technique on compressed images such as videos from wearable egocentric cameras. For the task of word spotting, we have introduced a novel mid-level word representation method. We have proposed a technique to create and exploit an intermediate representation of images based on text attributes which roughly correspond to character probability maps. Our representation extends the concept of Pyramidal Histogram Of Characters (PHOC) by exploiting Fully Convolutional Networks to derive a pixel-wise mapping of the character distribution within candidate word regions. We call this representation the Soft-PHOC. Furthermore, we show how to use Soft-PHOC descriptors for word spotting tasks through an efficient text line proposal algorithm. To evaluate the detected text, we propose a novel line based evaluation along with the classic bounding box based approach. We test our method on incidental scene text images which comprises real-life scenarios such as urban scenes. The importance of incidental scene text images is due to the complexity of backgrounds, perspective, variety of script and language, short text and little linguistic context. All of these factors together makes the incidental scene text images challenging.
 
  Address November 2018  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Dimosthenis Karatzas;Andrew Bagdanov  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-948531-1-1 Medium  
  Area Expedition Conference  
  Notes DAG; 600.121 Approved no  
  Call Number Admin @ si @ Baz2018 Serial 3220  
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