Home | << 1 2 3 4 5 6 7 8 9 10 >> [11–12] |
Records | |||||
---|---|---|---|---|---|
Author | Francesco Ciompi; Simone Balocco; Carles Caus; J. Mauri; Petia Radeva | ||||
Title | Stent shape estimation through a comprehensive interpretation of intravascular ultrasound images | Type | Conference Article | ||
Year | 2013 | Publication | 16th International Conference on Medical Image Computing and Computer Assisted Intervention | Abbreviated Journal | |
Volume | 8150 | Issue | 2 | Pages | 345-352 |
Keywords | |||||
Abstract | We present a method for automatic struts detection and stent shape estimation in cross-sectional intravascular ultrasound images. A stent shape is first estimated through a comprehensive interpretation of the vessel morphology, performed using a supervised context-aware multi-class classification scheme. Then, the successive strut identification exploits both local appearance and the defined stent shape. The method is tested on 589 images obtained from 80 patients, achieving a F-measure of 74.1% and an averaged distance between manual and automatic struts of 0.10 mm. | ||||
Address | Nagoya; Japan; September 2013 | ||||
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 | 978-3-642-40762-8 | Medium | |
Area | Expedition | Conference | MICCAI | ||
Notes | MILAB | Approved | no | ||
Call Number | Admin @ si @ CBC2013 | Serial | 2258 | ||
Permanent link to this record | |||||
Author | Laura Igual; Xavier Baro | ||||
Title | Experiencia de aprendizaje de programación basada en proyectos. Simposio-Taller Estrategias y herramientas para el aprendizaje y la evaluación | Type | Miscellaneous | ||
Year | 2013 | Publication | Simposio-Taller Estrategias y herramientas para el aprendizaje y la evaluación, de las XIX Jornadas sobre la Enseñanza Universitaria de la Informática | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | |||||
Abstract | |||||
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 | Medium | |||
Area | Expedition | Conference | JENUI | ||
Notes | OR;HuPBA;MV | Approved | no | ||
Call Number | Admin @ si @ IgB2013 | Serial | 2257 | ||
Permanent link to this record | |||||
Author | Santiago Segui; Laura Igual; Jordi Vitria | ||||
Title | Bagged One Class Classifiers in the Presence of Outliers | Type | Journal Article | ||
Year | 2013 | Publication | International Journal of Pattern Recognition and Artificial Intelligence | Abbreviated Journal | IJPRAI |
Volume | 27 | Issue | 5 | Pages | 1350014-1350035 |
Keywords | One-class Classifier; Ensemble Methods; Bagging and Outliers | ||||
Abstract | The problem of training classifiers only with target data arises in many applications where non-target data are too costly, difficult to obtain, or not available at all. Several one-class classification methods have been presented to solve this problem, but most of the methods are highly sensitive to the presence of outliers in the target class. Ensemble methods have therefore been proposed as a powerful way to improve the classification performance of binary/multi-class learning algorithms by introducing diversity into classifiers.
However, their application to one-class classification has been rather limited. In this paper, we present a new ensemble method based on a non-parametric weighted bagging strategy for one-class classification, to improve accuracy in the presence of outliers. While the standard bagging strategy assumes a uniform data distribution, the method we propose here estimates a probability density based on a forest structure of the data. This assumption allows the estimation of data distribution from the computation of simple univariate and bivariate kernel densities. Experiments using original and noisy versions of 20 different datasets show that bagging ensemble methods applied to different one-class classifiers outperform base one-class classification methods. Moreover, we show that, in noisy versions of the datasets, the non-parametric weighted bagging strategy we propose outperforms the classical bagging strategy in a statistically significant way. |
||||
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 | Medium | |||
Area | Expedition | Conference | |||
Notes | OR; 600.046;MV | Approved | no | ||
Call Number | Admin @ si @ SIV2013 | Serial | 2256 | ||
Permanent link to this record | |||||
Author | S.Grau; Anna Puig; Sergio Escalera; Maria Salamo; Oscar Amoros | ||||
Title | Efficient complementary viewpoint selection in volume rendering | Type | Conference Article | ||
Year | 2013 | Publication | 21st WSCG Conference on Computer Graphics, | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Dual camera; Visualization; Interactive Interfaces; Dynamic Time Warping. | ||||
Abstract | A major goal of visualization is to appropriately express knowledge of scientific data. Generally, gathering visual information contained in the volume data often requires a lot of expertise from the final user to setup the parameters of the visualization. One way of alleviating this problem is to provide the position of inner structures with different viewpoint locations to enhance the perception and construction of the mental image. To this end, traditional illustrations use two or three different views of the regions of interest. Similarly, with the aim of assisting the users to easily place a good viewpoint location, this paper proposes an automatic and interactive method that locates different complementary viewpoints from a reference camera in volume datasets. Specifically, the proposed method combines the quantity of information each camera provides for each structure and the shape similarity of the projections of the remaining viewpoints based on Dynamic Time Warping. The selected complementary viewpoints allow a better understanding of the focused structure in several applications. Thus, the user interactively receives feedback based on several viewpoints that helps him to understand the visual information. A live-user evaluation on different data sets show a good convergence to useful complementary viewpoints. | ||||
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 | 978-808694374-9 | Medium | ||
Area | Expedition | Conference | WSCG | ||
Notes | HuPBA; 600.046;MILAB | Approved | no | ||
Call Number | Admin @ si @ GPE2013a | Serial | 2255 | ||
Permanent link to this record | |||||
Author | Andreas Møgelmose; Chris Bahnsen; Thomas B. Moeslund; Albert Clapes; Sergio Escalera | ||||
Title | Tri-modal Person Re-identification with RGB, Depth and Thermal Features | Type | Conference Article | ||
Year | 2013 | Publication | 9th IEEE Workshop on Perception beyond the visible Spectrum, Computer Vision and Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 301-307 | ||
Keywords | |||||
Abstract | Person re-identification is about recognizing people who have passed by a sensor earlier. Previous work is mainly based on RGB data, but in this work we for the first time present a system where we combine RGB, depth, and thermal data for re-identification purposes. First, from each of the three modalities, we obtain some particular features: from RGB data, we model color information from different regions of the body, from depth data, we compute different soft body biometrics, and from thermal data, we extract local structural information. Then, the three information types are combined in a joined classifier. The tri-modal system is evaluated on a new RGB-D-T dataset, showing successful results in re-identification scenarios. | ||||
Address | Portland; oregon; June 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 | 978-0-7695-4990-3 | Medium | ||
Area | Expedition | Conference | CVPRW | ||
Notes | HUPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ MBM2013 | Serial | 2253 | ||
Permanent link to this record | |||||
Author | Miguel Reyes; Albert Clapes; Jose Ramirez; Juan R Revilla; Sergio Escalera | ||||
Title | Automatic Digital Biometry Analysis based on Depth Maps | Type | Journal Article | ||
Year | 2013 | Publication | Computers in Industry | Abbreviated Journal | COMPUTIND |
Volume | 64 | Issue | 9 | Pages | 1316-1325 |
Keywords | Multi-modal data fusion; Depth maps; Posture analysis; Anthropometric data; Musculo-skeletal disorders; Gesture analysis | ||||
Abstract | World Health Organization estimates that 80% of the world population is affected by back-related disorders during his life. Current practices to analyze musculo-skeletal disorders (MSDs) are expensive, subjective, and invasive. In this work, we propose a tool for static body posture analysis and dynamic range of movement estimation of the skeleton joints based on 3D anthropometric information from multi-modal data. Given a set of keypoints, RGB and depth data are aligned, depth surface is reconstructed, keypoints are matched, and accurate measurements about posture and spinal curvature are computed. Given a set of joints, range of movement measurements is also obtained. Moreover, gesture recognition based on joint movements is performed to look for the correctness in the development of physical exercises. The system shows high precision and reliable measurements, being useful for posture reeducation purposes to prevent MSDs, as well as tracking the posture evolution of patients in rehabilitation treatments. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Elsevier | 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 | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ RCR2013 | Serial | 2252 | ||
Permanent link to this record | |||||
Author | Daniel Sanchez; J.C.Ortega; Miguel Angel Bautista | ||||
Title | Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization | Type | Conference Article | ||
Year | 2013 | Publication | 6th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 7887 | Issue | Pages | 50-58 | |
Keywords | Human Body Segmentation; Error-Correcting Output Codes; Cascade of Classifiers; Graph Cuts | ||||
Abstract | Human body segmentation is a hard task because of the high variability in appearance produced by changes in the point of view, lighting conditions, and number of articulations of the human body. In this paper, we propose a two-stage approach for the segmentation of the human body. In a first step, a set of human limbs are described, normalized to be rotation invariant, and trained using cascade of classifiers to be split in a tree structure way. Once the tree structure is trained, it is included in a ternary Error-Correcting Output Codes (ECOC) framework. This first classification step is applied in a windowing way on a new test image, defining a body-like probability map, which is used as an initialization of a GMM color modelling and binary Graph Cuts optimization procedure. The proposed methodology is tested in a novel limb-labelled data set. Results show performance improvements of the novel approach in comparison to classical cascade of classifiers and human detector-based Graph Cuts segmentation approaches. | ||||
Address | Madeira; Portugal; June 2013 | ||||
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 | 978-3-642-38627-5 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | HUPBA | Approved | no | ||
Call Number | SOB2013 | Serial | 2250 | ||
Permanent link to this record | |||||
Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
Title | Logo recognition Based on the Dempster-Shafer Fusion of Multiple Classifiers | Type | Conference Article | ||
Year | 2013 | Publication | 26th Canadian Conference on Artificial Intelligence | Abbreviated Journal | |
Volume | 7884 | Issue | Pages | 1-12 | |
Keywords | Logo recognition; ensemble classification; Dempster-Shafer fusion; Zernike moments; generic Fourier descriptor; shape signature | ||||
Abstract | Best paper award
The performance of different feature extraction and shape description methods in trademark image recognition systems have been studied by several researchers. However, the potential improvement in classification through feature fusion by ensemble-based methods has remained unattended. In this work, we evaluate the performance of an ensemble of three classifiers, each trained on different feature sets. Three promising shape description techniques, including Zernike moments, generic Fourier descriptors, and shape signature are used to extract informative features from logo images, and each set of features is fed into an individual classifier. In order to reduce recognition error, a powerful combination strategy based on the Dempster-Shafer theory is utilized to fuse the three classifiers trained on different sources of information. This combination strategy can effectively make use of diversity of base learners generated with different set of features. The recognition results of the individual classifiers are compared with those obtained from fusing the classifiers’ output, showing significant performance improvements of the proposed methodology. |
||||
Address | Canada; May 2013 | ||||
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 | 0302-9743 | ISBN | 978-3-642-38456-1 | Medium | |
Area | Expedition | Conference | AI | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BGE2013b | Serial | 2249 | ||
Permanent link to this record | |||||
Author | Albert Clapes; Miguel Reyes; Sergio Escalera | ||||
Title | Multi-modal User Identification and Object Recognition Surveillance System | Type | Journal Article | ||
Year | 2013 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 34 | Issue | 7 | Pages | 799-808 |
Keywords | Multi-modal RGB-Depth data analysis; User identification; Object recognition; Intelligent surveillance; Visual features; Statistical learning | ||||
Abstract | We propose an automatic surveillance system for user identification and object recognition based on multi-modal RGB-Depth data analysis. We model a RGBD environment learning a pixel-based background Gaussian distribution. Then, user and object candidate regions are detected and recognized using robust statistical approaches. The system robustly recognizes users and updates the system in an online way, identifying and detecting new actors in the scene. Moreover, segmented objects are described, matched, recognized, and updated online using view-point 3D descriptions, being robust to partial occlusions and local 3D viewpoint rotations. Finally, the system saves the historic of user–object assignments, being specially useful for surveillance scenarios. The system has been evaluated on a novel data set containing different indoor/outdoor scenarios, objects, and users, showing accurate recognition and better performance than standard state-of-the-art approaches. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Elsevier | 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 | HUPBA; 600.046; 605.203;MILAB | Approved | no | ||
Call Number | Admin @ si @ CRE2013 | Serial | 2248 | ||
Permanent link to this record | |||||
Author | Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera | ||||
Title | A Genetic-based Subspace Analysis Method for Improving Error-Correcting Output Coding | Type | Journal Article | ||
Year | 2013 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 46 | Issue | 10 | Pages | 2830-2839 |
Keywords | Error Correcting Output Codes; Evolutionary computation; Multiclass classification; Feature subspace; Ensemble classification | ||||
Abstract | Two key factors affecting the performance of Error Correcting Output Codes (ECOC) in multiclass classification problems are the independence of binary classifiers and the problem-dependent coding design. In this paper, we propose an evolutionary algorithm-based approach to the design of an application-dependent codematrix in the ECOC framework. The central idea of this work is to design a three-dimensional codematrix, where the third dimension is the feature space of the problem domain. In order to do that, we consider the feature space in the design process of the codematrix with the aim of improving the independence and accuracy of binary classifiers. The proposed method takes advantage of some basic concepts of ensemble classification, such as diversity of classifiers, and also benefits from the evolutionary approach for optimizing the three-dimensional codematrix, taking into account the problem domain. We provide a set of experimental results using a set of benchmark datasets from the UCI Machine Learning Repository, as well as two real multiclass Computer Vision problems. Both sets of experiments are conducted using two different base learners: Neural Networks and Decision Trees. The results show that the proposed method increases the classification accuracy in comparison with the state-of-the-art ECOC coding techniques. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Elsevier | 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 | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ BGE2013a | Serial | 2247 | ||
Permanent link to this record | |||||
Author | Fernando Barrera; Felipe Lumbreras; Angel Sappa | ||||
Title | Multispectral Piecewise Planar Stereo using Manhattan-World Assumption | Type | Journal Article | ||
Year | 2013 | Publication | Pattern Recognition Letters | Abbreviated Journal | PRL |
Volume | 34 | Issue | 1 | Pages | 52-61 |
Keywords | Multispectral stereo rig; Dense disparity maps from multispectral stereo; Color and infrared images | ||||
Abstract | This paper proposes a new framework for extracting dense disparity maps from a multispectral stereo rig. The system is constructed with an infrared and a color camera. It is intended to explore novel multispectral stereo matching approaches that will allow further extraction of semantic information. The proposed framework consists of three stages. Firstly, an initial sparse disparity map is generated by using a cost function based on feature matching in a multiresolution scheme. Then, by looking at the color image, a set of planar hypotheses is defined to describe the surfaces on the scene. Finally, the previous stages are combined by reformulating the disparity computation as a global minimization problem. The paper has two main contributions. The first contribution combines mutual information with a shape descriptor based on gradient in a multiresolution scheme. The second contribution, which is based on the Manhattan-world assumption, extracts a dense disparity representation using the graph cut algorithm. Experimental results in outdoor scenarios are provided showing the validity of the proposed framework. | ||||
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 | Medium | |||
Area | Expedition | Conference | |||
Notes | ADAS; 600.054; 600.055; 605.203 | Approved | no | ||
Call Number | Admin @ si @ BLS2013 | Serial | 2245 | ||
Permanent link to this record | |||||
Author | Naveen Onkarappa; Angel Sappa | ||||
Title | Laplacian Derivative based Regularization for Optical Flow Estimation in Driving Scenario | Type | Conference Article | ||
Year | 2013 | Publication | 15th International Conference on Computer Analysis of Images and Patterns | Abbreviated Journal | |
Volume | 8048 | Issue | Pages | 483-490 | |
Keywords | Optical flow; regularization; Driver Assistance Systems; Performance Evaluation | ||||
Abstract | Existing state of the art optical flow approaches, which are evaluated on standard datasets such as Middlebury, not necessarily have a similar performance when evaluated on driving scenarios. This drop on performance is due to several challenges arising on real scenarios during driving. Towards this direction, in this paper, we propose a modification to the regularization term in a variational optical flow formulation, that notably improves the results, specially in driving scenarios. The proposed modification consists on using the Laplacian derivatives of flow components in the regularization term instead of gradients of flow components. We show the improvements in results on a standard real image sequences dataset (KITTI). | ||||
Address | York; UK; August 2013 | ||||
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 | 978-3-642-40245-6 | Medium | |
Area | Expedition | Conference | CAIP | ||
Notes | ADAS; 600.055; 601.215 | Approved | no | ||
Call Number | Admin @ si @ OnS2013b | Serial | 2244 | ||
Permanent link to this record | |||||
Author | Naveen Onkarappa; Angel Sappa | ||||
Title | A Novel Space Variant Image Representation | Type | Journal Article | ||
Year | 2013 | Publication | Journal of Mathematical Imaging and Vision | Abbreviated Journal | JMIV |
Volume | 47 | Issue | 1-2 | Pages | 48-59 |
Keywords | Space-variant representation; Log-polar mapping; Onboard vision applications | ||||
Abstract | Traditionally, in machine vision images are represented using cartesian coordinates with uniform sampling along the axes. On the contrary, biological vision systems represent images using polar coordinates with non-uniform sampling. For various advantages provided by space-variant representations many researchers are interested in space-variant computer vision. In this direction the current work proposes a novel and simple space variant representation of images. The proposed representation is compared with the classical log-polar mapping. The log-polar representation is motivated by biological vision having the characteristic of higher resolution at the fovea and reduced resolution at the periphery. On the contrary to the log-polar, the proposed new representation has higher resolution at the periphery and lower resolution at the fovea. Our proposal is proved to be a better representation in navigational scenarios such as driver assistance systems and robotics. The experimental results involve analysis of optical flow fields computed on both proposed and log-polar representations. Additionally, an egomotion estimation application is also shown as an illustrative example. The experimental analysis comprises results from synthetic as well as real sequences. | ||||
Address | |||||
Corporate Author | Thesis | ||||
Publisher | Springer US | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0924-9907 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | ADAS; 600.055; 605.203; 601.215 | Approved | no | ||
Call Number | Admin @ si @ OnS2013a | Serial | 2243 | ||
Permanent link to this record | |||||
Author | Olivier Penacchio; Xavier Otazu; Laura Dempere-Marco | ||||
Title | A Neurodynamical Model of Brightness Induction in V1 | Type | Journal Article | ||
Year | 2013 | Publication | PloS ONE | Abbreviated Journal | Plos |
Volume | 8 | Issue | 5 | Pages | e64086 |
Keywords | |||||
Abstract | Brightness induction is the modulation of the perceived intensity of an area by the luminance of surrounding areas. Recent neurophysiological evidence suggests that brightness information might be explicitly represented in V1, in contrast to the more common assumption that the striate cortex is an area mostly responsive to sensory information. Here we investigate possible neural mechanisms that offer a plausible explanation for such phenomenon. To this end, a neurodynamical model which is based on neurophysiological evidence and focuses on the part of V1 responsible for contextual influences is presented. The proposed computational model successfully accounts for well known psychophysical effects for static contexts and also for brightness induction in dynamic contexts defined by modulating the luminance of surrounding areas. This work suggests that intra-cortical interactions in V1 could, at least partially, explain brightness induction effects and reveals how a common general architecture may account for several different fundamental processes, such as visual saliency and brightness induction, which emerge early in the visual processing pathway. | ||||
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 | Medium | |||
Area | Expedition | Conference | |||
Notes | CIC | Approved | no | ||
Call Number | Admin @ si @ POD2013 | Serial | 2242 | ||
Permanent link to this record | |||||
Author | Alicia Fornes; Xavier Otazu; Josep Llados | ||||
Title | Show through cancellation and image enhancement by multiresolution contrast processing | Type | Conference Article | ||
Year | 2013 | Publication | 12th International Conference on Document Analysis and Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 200-204 | ||
Keywords | |||||
Abstract | Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are developed to solve these problems, and in the case of show-through, by scanning and matching both the front and back sides of the document. In contrast, our approach is designed to use only one side of the scanned document. We hypothesize that show-trough are low contrast components, while foreground components are high contrast ones. A Multiresolution Contrast (MC) decomposition is presented in order to estimate the contrast of features at different spatial scales. We cancel the show-through phenomenon by thresholding these low contrast components. This decomposition is also able to enhance the image removing shadowed areas by weighting spatial scales. Results show that the enhanced images improve the readability of the documents, allowing scholars both to recover unreadable words and to solve ambiguities. | ||||
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; 602.006; 600.045; 600.061; 600.052;CIC | Approved | no | ||
Call Number | Admin @ si @ FOL2013 | Serial | 2241 | ||
Permanent link to this record |