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检索条件"机构=Image and Pattern Recognition Laboratory"

共 663 条记录，以下是411-420 订阅

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Multi-regularization parameters estimation for Gaussian mixture classifier based on MDL principle

Multi-regularization parameters estimation for Gaussian mixt...

引用

International Conference on Neural Computation Theory and Applications, NCTA 2011

作者： Zhou, Xiuling Guo, Ping Philip Chen, C.L. Laboratory of Image Processing and Pattern Recognition Beijing Normal University Beijing 100875 China Artificial Intelligence Institute Beijing City University Beijing China Faculty of Science and Technology University of Macau Macau China

ISBN: (纸本)9789898425843

Regularization is a solution to solve the problem of unstable estimation of covariance matrix with a small sample set in Gaussian classifier. And multi-regularization parameters estimation is more difficult than single parameter estimation. In this paper, KLIM-L covariance matrix estimation is derived theoretically based on MDL (minimum description length) principle for the small sample problem with high dimension. KLIM-L is a generalization of KLIM (Kullback-Leibler information measure) which considers the local difference in each dimension. Under the framework of MDL principle, multi-regularization parameters are selected by the criterion of minimization the KL divergence and estimated simply and directly by point estimation which is approximated by two-order Taylor expansion. It costs less computation time to estimate the multi-regularization parameters in KLIM-L than in RDA (regularized discriminant analysis) and in LOOC (leave-one-out covariance matrix estimate) where cross validation technique is adopted. And higher classification accuracy is achieved by the proposed KLIM-L estimator in experiment.

关键词： Parameter estimation

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An effective document image deblurring algorithm

An effective document image deblurring algorithm

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作者： Chen, Xiaogang He, Xiangjian Yang, Jie Wu, Qiang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Centre for Innovation in IT Services and Applications University of Technology Sydney Australia Key Laboratory of System Control and Information Processing Ministry of Education China

ISBN: (纸本)9781457703942

Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method. © 2011 IEEE.

关键词： image enhancement

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Information theoretic preattentive saliency: A closed-form solution

Information theoretic preattentive saliency: A closed-form s...

引用

International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Marco Loog Image Group University of Copenhagen Denmark Pattern Recognition laboratory Delft University of Technology Netherlands

Employing an information theoretic operational definition of bottom-up attention from the field of computational visual perception, a very general expression for saliency is provided. As opposed to many of the current approaches to determining a saliency map, there is no need for an explicit, data-driven density estimation. Given the features, descriptors, or filter bank that one wants to use to describe the image content at every position, we provide a closed-form expression for the associated saliency at that location. This, indeed, makes explicit that what is considered salient depends on how, i.e., by means of which features, image information is described. We illustrate our result by determining a few specific saliency maps based on particular choices of features. One of them makes the link with the mapping underlying well-known Harris interest points, which is a result recently obtained in isolation. Another choice of features is, rather loosely, inspired by the success of histogram of oriented gradient descriptors and proves to provide state-of-the-art results on a collaborative benchmark for region of interest detection.

关键词： Feature extraction Computer vision Visualization Closed-form solutions image color analysis Equations Vectors

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Maintaining imbalance highly dependent medical data using dirichlet process data generation

Maintaining imbalance highly dependent medical data using di...

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International Conference on Digital Information Management (ICDIM)

作者： Tieta Antaresti Mohamad Ivan Fanany Aniati Murni Arymurthy Pattern Recognition Image Processing and Content-Based Image Retrieval Laboratory Faculty of Computer Science Universitas Indonesia Depok Indonesia

The existence of imbalanced data between one class and another class is an important issue to be considered in a classification problem. One of the well-known data balancing technique is the artificial oversampling, which increase the size of datasets. In this research, multinomial classification was applied to classify some recorded features obtained from a single ECG (electrocardiograph) sensor. Therefore, a Dirichlet process, a dirichlet distribution of cumulative distribution function of each data partition, was needed to model the distribution of the new generated data by also considering the statistical properties of the previous data. Data balancing process had given the result of 77.21% classification accuracy (CA), and 90.9% area under ROC curve (AUC).

关键词： Electrocardiography Accuracy Diseases Data models Bayesian methods Sleep apnea Machine learning

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Restoration of Arbitrarily Warped Historical Document images Using Flow Lines

Restoration of Arbitrarily Warped Historical Document Images...

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International Conference on Document Analysis and recognition

作者： Maryam Rahnemoonfar Apostolos Antonacopoulos Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford UK

ISBN: (纸本)9781457713507

Historical documents frequently suffer from arbitrary geometric distortions (warping and folds) due to storage conditions, use and to, some extent, the printing process of the time. In addition, page curl can be prominent due to the scanning technique used. Such distortions adversely affect OCR and print-on-demand quality. Previous approaches to geometric restoration either focus only on the correction of page curl or require supplementary information obtained by additional scanning hardware - not practical for existing scans. This paper presents a new approach to detect and restore arbitrary warping and folds, in addition to page curl. Warped text lines and the smooth deformation between them are precisely modelled as primary and secondary flow lines that are then restored to their original linear shape. Preliminary, but representative, experimental results, in comparison to a leading page curl removal method and an industry-standard commercial system, demonstrate the effectiveness of the proposed method.

关键词： Text analysis

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Interactive object segmentation using iterative adjustable graph cut

Interactive object segmentation using iterative adjustable g...

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2011 IEEE Visual Communications and image Processing, VCIP 2011

作者： Shi, Ran Liu, Zhi Xue, Yinzhu Zhang, Xiang School of Communication and Information Engineering Shanghai University Shanghai 200072 China Key Laboratory of Advanced Display and System Application Shanghai University Ministry of Education Shanghai 200072 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China

ISBN: (纸本)9781457713200

Interactive object segmentation is widely used for extracting any user-interested objects from natural images. A common problem with many interactive segmentation approaches is that the object segmentation quality is degraded due to inaccurate object/background seeds provided by the user. This paper proposes an iterative adjustable graph cut to efficiently solve this problem. First, object/background seeds are initialized based on the object segmentation result obtained with the user-specified scribbles as the interactive input. Then, an iterative seed adjustment scheme is exploited to correct inaccurate seeds and extract new suitable seeds via graph cut, in which the balancing weight between energy terms are adaptively updated to protect stable seeds and speedup the iteration process. Finally, suitable seeds are obtained and graph cut is used to segment the objects. Experimental results demonstrate the better segmentation performance of our approach even if user provides rather rough seeds. © 2011 IEEE.

关键词： image segmentation

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Historical Document Layout Analysis Competition

Historical Document Layout Analysis Competition

引用

International Conference on Document Analysis and recognition

作者： A. Antonacopoulos C. Clausner C. Papadopoulos S. Pletschacher Pattern Recognition and Image Analysis (PRImA) Research Laboratory School of Computing Science and Engineering University of Salford Greater Manchester UK

ISBN: (纸本)9781457713507

This paper presents an objective comparative evaluation of layout analysis methods for scanned historical documents. It describes the competition (modus operandi, dataset and evaluation methodology) held in the context of ICDAR2011 and the International Workshop on Historical Document Imaging and Processing (HIP2011), presenting the results of the evaluation of four submitted methods. A commercial state-of-the-art system is also evaluated for comparison. Two scenarios are reported in this paper, one evaluating the ability of methods to accurately segment regions and the other evaluating the whole pipeline of segmentation and region classification (with a text extraction goal). The results indicate that there is a convergence to a certain methodology with some variations in the approach. However, there is still a considerable need to develop robust methods that deal with the idiosyncrasies of historical documents.

关键词： Layout Particle separators Text analysis Performance evaluation Libraries image segmentation Corporate acquisitions

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The influence of hubness on nearest-neighbor methods in object recognition

The influence of hubness on nearest-neighbor methods in obje...

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IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)

作者： Nenad Tomašev Raluca Brehar Dunja Mladenić Sergiu Nedevschi Jožef Stefan Institute Artificial Intelligence Laboratory Ljubljana Slovenia Image Processing and Pattern Recognition Group Technical University of Cluj-Napoca Romania

Object recognition from images is one of the essential problems in automatic image processing. In this paper we focus specifically on nearest neighbor methods, which are widely used in many practical applications, not necessarily related to image data. It has recently come to attention that high dimensional data also exhibit high hubness, which essentially means that some very influential data points appear and these points are referred to as hubs. Unsurprisingly, hubs play a very important role in the nearest neighbor classification. We examine the hubness of various image data sets, under several different feature representations. We also show that it is possible to exploit the observed hubness and improve the recognition accuracy.

关键词： Feature extraction Object recognition Entropy Histograms Visualization image color analysis Shape

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An effective document image deblurring algorithm

An effective document image deblurring algorithm

引用

Conference on Computer Vision and pattern recognition (CVPR)

作者： Xiaogang Chen Xiangjian He Jie Yang Qiang Wu Key Laboratory of System Control and Information Processing Ministry of Education China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China Centre of Innovation in IT Services and Applications University of Technology Sydney Australia

关键词： image restoration Histograms TV Object segmentation Deconvolution Estimation image segmentation

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Predicting functional impact of single amino acid polymorphisms by integrating sequence and structural features

Predicting functional impact of single amino acid polymorphi...

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5th IEEE International Conference on Systems Biology, ISB 2011

作者： Wang, Mingjun Shen, Hong-Bin Akutsu, Tatsuya Song, Jiangning State Engineering Laboratory for Industrial Enzymes Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences Tianjin 300308 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto 611-0011 Japan Department of Biochemistry and Molecular Biology Faculty of Medicine Monash University Melbourne VIC 3800 Australia

ISBN: (纸本)9781457716669

Single amino acid polymorphisms (SAPs) are the most abundant form of known genetic variations associated with human diseases. It is of great interest to study the sequence-structure-function relationship underlying SAPs. In this work, we collected the human variant data from three databases and divided them into three categories, i.e. cancer somatic mutations (CSM), Mendelian disease-related variant (SVD) and neutral polymorphisms (SVP). We built support vector machine (SVM) classifiers to predict these three classes of SAPs, using the optimal features selected by a random forest algorithm. Consequently, 280 sequence-derived and structural features were initially extracted from the curated datasets from which 18 optimal candidate features were further selected by random forest. Furthermore, we performed a stepwise feature selection to select characteristic sequence and structural features that are important for predicting each SAPs class. As a result, our predictors achieved a prediction accuracy (ACC) of 84.97, 96.93, 86.98 and 88.24%, for the three classes, CSM, SVD and SVP, respectively. Performance comparison with other previously developed tools such as SIFT, SNAP and Polyphen2 indicates that our method provides a favorable performance with higher Sensitivity scores and Matthew's correlation coefficients (MCC). These results indicate that the prediction performance of SAPs classifiers can be effectively improved by feature selection. Moreover, division of SAPs into three respective categories and construction of accurate SVM-based classifiers for each class provides a practically useful way for investigating the difference between Mendelian disease-related variants and cancer somatic mutations. © 2011 IEEE.

关键词： Amino acids

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