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David Fernandez, Jon Almazan, Nuria Cirera, Alicia Fornes and Josep Llados. 2014. BH2M: the Barcelona Historical Handwritten Marriages database. 22nd International Conference on Pattern Recognition.256–261.
Abstract: This paper presents an image database of historical handwritten marriages records stored in the archives of Barcelona cathedral, and the corresponding meta-data addressed to evaluate the performance of document analysis algorithms. The contribution of this paper is twofold. First, it presents a complete ground truth which covers the whole pipeline of handwriting
recognition research, from layout analysis to recognition and understanding. Second, it is the first dataset in the emerging area of genealogical document analysis, where documents are manuscripts pseudo-structured with specific lexicons and the interest is beyond pure transcriptions but context dependent.
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David Fernandez, Josep Llados and Alicia Fornes. 2011. Handwritten Word Spotting in Old Manuscript Images Using a Pseudo-Structural Descriptor Organized in a Hash Structure. In Jordi Vitria, Joao Miguel Raposo and Mario Hernandez, eds. 5th Iberian Conference on Pattern Recognition and Image Analysis.628–635.
Abstract: There are lots of historical handwritten documents with information that can be used for several studies and projects. The Document Image Analysis and Recognition community is interested in preserving these documents and extracting all the valuable information from them. Handwritten word-spotting is the pattern classification task which consists in detecting handwriting word images. In this work, we have used a query-by-example formalism: we have matched an input image with one or multiple images from handwritten documents to determine the distance that might indicate a correspondence. We have developed an approach based in characteristic Loci Features stored in a hash structure. Document images of the marriage licences of the Cathedral of Barcelona are used as the benchmarking database.
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David Fernandez, Josep Llados and Alicia Fornes. 2014. A graph-based approach for segmenting touching lines in historical handwritten documents. IJDAR, 17(3), 293–312.
Abstract: Text line segmentation in handwritten documents is an important task in the recognition of historical documents.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.
Keywords: Text line segmentation; Handwritten documents; Document image processing; Historical document analysis
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David Fernandez, Josep Llados, Alicia Fornes and R.Manmatha. 2012. On Influence of Line Segmentation in Efficient Word Segmentation in Old Manuscripts. 13th International Conference on Frontiers in Handwriting Recognition.763–768.
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%
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
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David Fernandez, Pau Riba, Alicia Fornes and Josep Llados. 2014. On the Influence of Key Point Encoding for Handwritten Word Spotting. 14th International Conference on Frontiers in Handwriting Recognition.476–481.
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.
Keywords: Local descriptors; Interest points; Handwritten documents; Word spotting; Historical document analysis
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David Fernandez, R.Manmatha, Josep Llados and Alicia Fornes. 2014. Sequential Word Spotting in Historical Handwritten Documents. 11th IAPR International Workshop on Document Analysis and Systems.101–105.
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.
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David Fernandez, Simone Marinai, Josep Llados and Alicia Fornes. 2013. Contextual Word Spotting in Historical Manuscripts using Markov Logic Networks. 2nd International Workshop on Historical Document Imaging and Processing.36–43.
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.
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Debora Gil, Jordi Gonzalez and Gemma Sanchez, eds. 2007. Computer Vision: Advances in Research and Development. Bellaterra (Spain), UAB. (2.)
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Debora Gil, Oriol Ramos Terrades and Raquel Perez. 2020. Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution. Women in Geometry and Topology.
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Debora Gil, Oriol Ramos Terrades and Raquel Perez. 2021. Topological Radiomics (TOPiomics): Early Detection of Genetic Abnormalities in Cancer Treatment Evolution. Extended Abstracts GEOMVAP 2019, Trends in Mathematics 15. Springer Nature, 89–93.
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.
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