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Author | Thanh Ha Do; Oriol Ramos Terrades; Salvatore Tabbone | ||||
Title | DSD: document sparse-based denoising algorithm | Type | Journal Article | ||
Year | 2019 | Publication ![]() |
Pattern Analysis and Applications | Abbreviated Journal | PAA |
Volume | 22 | Issue | 1 | Pages | 177–186 |
Keywords | Document denoising; Sparse representations; Sparse dictionary learning; Document degradation models | ||||
Abstract | In this paper, we present a sparse-based denoising algorithm for scanned documents. This method can be applied to any kind of scanned documents with satisfactory results. Unlike other approaches, the proposed approach encodes noise documents through sparse representation and visual dictionary learning techniques without any prior noise model. Moreover, we propose a precision parameter estimator. Experiments on several datasets demonstrate the robustness of the proposed approach compared to the state-of-the-art methods on document denoising. | ||||
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Notes | DAG; 600.097; 600.140; 600.121 | Approved | no | ||
Call Number | Admin @ si @ DRT2019 | Serial | 3254 | ||
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Author | Agata Lapedriza; Santiago Segui; David Masip; Jordi Vitria | ||||
Title | A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning | Type | Journal | ||
Year | 2008 | Publication ![]() |
Pattern Analysis and Applications, Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications, | Abbreviated Journal | |
Volume | 11 | Issue | 3-4 | Pages | 299-308 |
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Publisher | Springer | Place of Publication | Editor | ||
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Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ LSM2008 | Serial | 996 | ||
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Author | David Masip; Ludmila I. Kuncheva; Jordi Vitria | ||||
Title | An ensemble-based method for linear feature extraction for two-class problems | Type | Journal | ||
Year | 2005 | Publication ![]() |
Pattern Analysis and Applications, 8(3): 227–237 (IF: 0.782) | Abbreviated Journal | |
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Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ MKV2005 | Serial | 613 | ||
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Author | F. Pla; Petia Radeva; Jordi Vitria | ||||
Title | Non-parametric distance-based classification techniques and their applications | Type | Journal | ||
Year | 2008 | Publication ![]() |
Pattern Analysis and Applications, Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications | Abbreviated Journal | |
Volume | 11 | Issue | 3-4 | Pages | 223–225 |
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Publisher | Springer | Place of Publication | Editor | ||
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Notes | OR;MILAB;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ PRV2008 | Serial | 999 | ||
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Author | Bogdan Raducanu; Jordi Vitria | ||||
Title | Online Nonparametric Discriminant Analysis for Incremental Subspace Learning and Recognition | Type | Journal | ||
Year | 2008 | Publication ![]() |
Pattern Analysis and Applications. Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications | Abbreviated Journal | |
Volume | 11 | Issue | 3-4 | Pages | 259–268 |
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Publisher | Springer | Place of Publication | Editor | ||
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Notes | OR;MV | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ RaV2008c | Serial | 997 | ||
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Author | Oriol Pujol; Sergio Escalera; Petia Radeva | ||||
Title | An Incremental Node Embedding Technique for Error Correcting Output Codes | Type | Journal | ||
Year | 2008 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 41 | Issue | 2 | Pages | 713–725 |
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Notes | MILAB;HuPBA | Approved | no | ||
Call Number | BCNPCL @ bcnpcl @ PER2008 | Serial | 942 | ||
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Author | Jose Antonio Rodriguez; Florent Perronnin | ||||
Title | Handwritten word-spotting using hidden Markov models and universal vocabularies | Type | Journal Article | ||
Year | 2009 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 42 | Issue | 9 | Pages | 2103-2116 |
Keywords | Word-spotting; Hidden Markov model; Score normalization; Universal vocabulary; Handwriting recognition | ||||
Abstract | Handwritten word-spotting is traditionally viewed as an image matching task between one or multiple query word-images and a set of candidate word-images in a database. This is a typical instance of the query-by-example paradigm. In this article, we introduce a statistical framework for the word-spotting problem which employs hidden Markov models (HMMs) to model keywords and a Gaussian mixture model (GMM) for score normalization. We explore the use of two types of HMMs for the word modeling part: continuous HMMs (C-HMMs) and semi-continuous HMMs (SC-HMMs), i.e. HMMs with a shared set of Gaussians. We show on a challenging multi-writer corpus that the proposed statistical framework is always superior to a traditional matching system which uses dynamic time warping (DTW) for word-image distance computation. A very important finding is that the SC-HMM is superior when labeled training data is scarce—as low as one sample per keyword—thanks to the prior information which can be incorporated in the shared set of Gaussians. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
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Series Volume | Series Issue | Edition | |||
ISSN | 0031-3203 | ISBN | Medium | ||
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Notes | Approved | no | |||
Call Number | Admin @ si @ RoP2009 | Serial | 1053 | ||
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Author | Ignasi Rius; Jordi Gonzalez; Javier Varona; Xavier Roca | ||||
Title | Action-specific motion prior for efficient bayesian 3D human body tracking | Type | Journal Article | ||
Year | 2009 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 42 | Issue | 11 | Pages | 2907–2921 |
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Abstract | In this paper, we aim to reconstruct the 3D motion parameters of a human body
model from the known 2D positions of a reduced set of joints in the image plane. Towards this end, an action-specific motion model is trained from a database of real motion-captured performances. The learnt motion model is used within a particle filtering framework as a priori knowledge on human motion. First, our dynamic model guides the particles according to similar situations previously learnt. Then, the solution space is constrained so only feasible human postures are accepted as valid solutions at each time step. As a result, we are able to track the 3D configuration of the full human body from several cycles of walking motion sequences using only the 2D positions of a very reduced set of joints from lateral or frontal viewpoints. |
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ISSN | 0031-3203 | ISBN | Medium | ||
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Notes | ISE | Approved | no | ||
Call Number | ISE @ ise @ RGV2009 | Serial | 1159 | ||
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Author | Miquel Ferrer; Ernest Valveny; F. Serratosa | ||||
Title | Median Graphs: A Genetic Approach based on New Theoretical Properties | Type | Journal Article | ||
Year | 2009 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 42 | Issue | 9 | Pages | 2003–2012 |
Keywords | Median graph; Genetic search; Maximum common subgraph; Graph matching; Structural pattern recognition | ||||
Abstract | Given a set of graphs, the median graph has been theoretically presented as a useful concept to infer a representative of the set. However, the computation of the median graph is a highly complex task and its practical application has been very limited up to now. In this work we present two major contributions. On one side, and from a theoretical point of view, we show new theoretical properties of the median graph. On the other side, using these new properties, we present a new approximate algorithm based on the genetic search, that improves the computation of the median graph. Finally, we perform a set of experiments on real data, where none of the existing algorithms for the median graph computation could be applied up to now due to their computational complexity. With these results, we show how the concept of the median graph can be used in real applications and leaves the box of the only-theoretical concepts, demonstrating, from a practical point of view, that can be a useful tool to represent a set of graphs. | ||||
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Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ FVS2009b | Serial | 1167 | ||
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Author | Daniel Ponsa; Antonio Lopez | ||||
Title | Variance reduction techniques in particle-based visual contour Tracking | Type | Journal Article | ||
Year | 2009 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 42 | Issue | 11 | Pages | 2372–2391 |
Keywords | Contour tracking; Active shape models; Kalman filter; Particle filter; Importance sampling; Unscented particle filter; Rao-Blackwellization; Partitioned sampling | ||||
Abstract | This paper presents a comparative study of three different strategies to improve the performance of particle filters, in the context of visual contour tracking: the unscented particle filter, the Rao-Blackwellized particle filter, and the partitioned sampling technique. The tracking problem analyzed is the joint estimation of the global and local transformation of the outline of a given target, represented following the active shape model approach. The main contributions of the paper are the novel adaptations of the considered techniques on this generic problem, and the quantitative assessment of their performance in extensive experimental work done. | ||||
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Notes | ADAS | Approved | no | ||
Call Number | ADAS @ adas @ PoL2009a | Serial | 1168 | ||
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Author | Miquel Ferrer; Ernest Valveny; F. Serratosa; K. Riesen; Horst Bunke | ||||
Title | Generalized Median Graph Computation by Means of Graph Embedding in Vector Spaces | Type | Journal Article | ||
Year | 2010 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 43 | Issue | 4 | Pages | 1642–1655 |
Keywords | Graph matching; Weighted mean of graphs; Median graph; Graph embedding; Vector spaces | ||||
Abstract | The median graph has been presented as a useful tool to represent a set of graphs. Nevertheless its computation is very complex and the existing algorithms are restricted to use limited amount of data. In this paper we propose a new approach for the computation of the median graph based on graph embedding. Graphs are embedded into a vector space and the median is computed in the vector domain. We have designed a procedure based on the weighted mean of a pair of graphs to go from the vector domain back to the graph domain in order to obtain a final approximation of the median graph. Experiments on three different databases containing large graphs show that we succeed to compute good approximations of the median graph. We have also applied the median graph to perform some basic classification tasks achieving reasonable good results. These experiments on real data open the door to the application of the median graph to a number of more complex machine learning algorithms where a representative of a set of graphs is needed. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
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Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ FVS2010 | Serial | 1294 | ||
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Author | Joan Mas; Josep Llados; Gemma Sanchez; J.A. Jorge | ||||
Title | A syntactic approach based on distortion-tolerant Adjacency Grammars and a spatial-directed parser to interpret sketched diagrams | Type | Journal Article | ||
Year | 2010 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 43 | Issue | 12 | Pages | 4148–4164 |
Keywords | Syntactic Pattern Recognition; Symbol recognition; Diagram understanding; Sketched diagrams; Adjacency Grammars; Incremental parsing; Spatial directed parsing | ||||
Abstract | This paper presents a syntactic approach based on Adjacency Grammars (AG) for sketch diagram modeling and understanding. Diagrams are a combination of graphical symbols arranged according to a set of spatial rules defined by a visual language. AG describe visual shapes by productions defined in terms of terminal and non-terminal symbols (graphical primitives and subshapes), and a set functions describing the spatial arrangements between symbols. Our approach to sketch diagram understanding provides three main contributions. First, since AG are linear grammars, there is a need to define shapes and relations inherently bidimensional using a sequential formalism. Second, our parsing approach uses an indexing structure based on a spatial tessellation. This serves to reduce the search space when finding candidates to produce a valid reduction. This allows order-free parsing of 2D visual sentences while keeping combinatorial explosion in check. Third, working with sketches requires a distortion model to cope with the natural variations of hand drawn strokes. To this end we extended the basic grammar with a distortion measure modeled on the allowable variation on spatial constraints associated with grammar productions. Finally, the paper reports on an experimental framework an interactive system for sketch analysis. User tests performed on two real scenarios show that our approach is usable in interactive settings. | ||||
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Publisher | Elsevier | Place of Publication | Editor | ||
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Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ MLS2010 | Serial | 1336 | ||
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Author | Umapada Pal; Partha Pratim Roy; N. Tripathya; Josep Llados | ||||
Title | Multi-oriented Bangla and Devnagari text recognition | Type | Journal Article | ||
Year | 2010 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 43 | Issue | 12 | Pages | 4124–4136 |
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Abstract | There are printed complex documents where text lines of a single page may have different orientations or the text lines may be curved in shape. As a result, it is difficult to detect the skew of such documents and hence character segmentation and recognition of such documents are a complex task. In this paper, using background and foreground information we propose a novel scheme towards the recognition of Indian complex documents of Bangla and Devnagari script. In Bangla and Devnagari documents usually characters in a word touch and they form cavity regions. To take care of these cavity regions, background information of such documents is used. Convex hull and water reservoir principle have been applied for this purpose. Here, at first, the characters are segmented from the documents using the background information of the text. Next, individual characters are recognized using rotation invariant features obtained from the foreground part of the characters.
For character segmentation, at first, writing mode of a touching component (word) is detected using water reservoir principle based features. Next, depending on writing mode and the reservoir base-region of the touching component, a set of candidate envelope points is then selected from the contour points of the component. Based on these candidate points, the touching component is finally segmented into individual characters. For recognition of multi-sized/multi-oriented characters the features are computed from different angular information obtained from the external and internal contour pixels of the characters. These angular information are computed in such a way that they do not depend on the size and rotation of the characters. Circular and convex hull rings have been used to divide a character into smaller zones to get zone-wise features for higher recognition results. We combine circular and convex hull features to improve the results and these features are fed to support vector machines (SVM) for recognition. From our experiment we obtained recognition results of 99.18% (98.86%) accuracy when tested on 7515 (7874) Devnagari (Bangla) characters. |
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Publisher | Elsevier | Place of Publication | Editor | ||
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Notes | DAG | Approved | no | ||
Call Number | DAG @ dag @ PRT2010 | Serial | 1337 | ||
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Author | Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta | ||||
Title | Structure-preserving smoothing of biomedical images | Type | Journal Article | ||
Year | 2011 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 44 | Issue | 9 | Pages | 1842-1851 |
Keywords | Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography | ||||
Abstract | Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. | ||||
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ISSN | 0031-3203 | ISBN | Medium | ||
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Notes | IAM; ADAS | Approved | no | ||
Call Number | IAM @ iam @ GHB2011 | Serial | 1526 | ||
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Author | Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal | ||||
Title | A Novel Mutual Nearest Neighbor based Symmetry for Text Frame Classification in Video | Type | Journal Article | ||
Year | 2011 | Publication ![]() |
Pattern Recognition | Abbreviated Journal | PR |
Volume | 44 | Issue | 8 | Pages | 1671-1683 |
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Abstract | In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection, etc. We propose a new text frame classification method that introduces a combination of wavelet and median moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max–Min clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called mutual nearest neighbor based symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created data show that the proposed method gives promising results in terms of recall and precision at the block and frame levels. Further, we also show how existing text detection methods tend to misclassify non-text frames as text frames in term of recall and precision at both the block and frame levels. | ||||
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Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ SDP2011 | Serial | 1727 | ||
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