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Sparse Representation for Multi-Label image Annotation

Sparse Representation for Multi-Label Image Annotation

引用

International Conference on Computational Intelligence and Security

作者： Bingxin Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781457720086

image annotation is the process of assigning proper keywords to describe the content of a given image, which can be regarded as a problem of multi-object image classification. In this paper, a general multi-label annotation algorithm is proposed, which is based on sparse representation theory and employs a multi-level decision method to deal with the multi-object classification problem. The experimental results show that the proposed algorithm can provide more promising results compared with the traditional classification based image annotation methods.

关键词： Training Vectors Support vector machines Databases Feature extraction Roads Training data

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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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Maintaining imbalance highly dependent medical data using dirichlet process data generation

Maintaining imbalance highly dependent medical data using di...

引用

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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Interactive object segmentation using iterative adjustable graph cut

Interactive object segmentation using iterative adjustable g...

引用

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

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

引用

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

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.

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...

引用

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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Interactive object segmentation using iterative adjustable graph cut

Interactive object segmentation using iterative adjustable g...

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IEEE Visual Communications and image processing (VCIP)

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

关键词： Object segmentation image segmentation Reliability Iterative methods Educational institutions image color analysis Error analysis

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Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segmentation Review

Ultrasound Carotid Artery Intima-Media Thickness (IMT) Segme...

引用

International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Xin Yang Jiaoying Jin Ming Yuchi Mingyue Ding State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence (IPRAI) Huazhong University of Science and Technology HUST Wuhan Hubei China Image Processing and Intelligence Control Key Laboratory of Education Ministry of China School of Life Science and Technology Huazhong University of Science and Technology HUST Wuhan Hubei China

Stroke and heart attack, which could be led by a kind of cerebrovascular and cardiovascular disease named asatherosclerosis, would seriously cause human morbidity and mortality. And the carotid artery of intima-media thickness (IMT) is a key indicator to the disease. With the development of computer assisted diagnosis (CAD) technology, Ultrasound imaging, being real-time, economic, reliable, safe, and now seems to become a standard in vascular assessment methodology especially for the measurement of IMT. This review is an attempt to discuss the clinical relevance of measurements in clinical practice at first, and then followed by the challenges that one has to face when approaching the segmentation of ultrasound images. Secondly, the paper is presentation of common used methods for the IMT segmentation and measurement. An overview of summary and future perspectives is given in conclusion finally.

关键词： Ultrasonic imaging image segmentation Carotid arteries Ultrasonic variables measurement Biomedical imaging

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Automatic Detection of the Intima-Media Layer in Ultrasound Common Carotid Artery image Based on Active Contour Model

Automatic Detection of the Intima-Media Layer in Ultrasound ...

引用

International Conference on Intelligent Computation and Bio-Medical Instrumentation (ICBMI)

作者： Jiaoying Jin Mingyue Ding Xin Yang Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Life School of Science and Technology Huazhong University of Science and Technology Wuhan China State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence(IPRAI) Life School of Science and Technology Huazhong University of Science and Technology Wuhan China

The analysis of the carotid artery wall is of paramount importance in clinical practice. Especially, the intima-media thickness is a risk index for some of the most severe acute cerebrovascular pathologies, hence, an accurate segmentation of the different layers of the carotid artery is needed. IMT is usually manually measured on longitudinal B-mode ultrasound images. In the past ten years, many computer-based techniques for intima-media thickness measurement have been proposed to overcome the limits of manual segmentation, but almost all of them require a certain degree of user interaction. In this paper we proposed a novel approach for the completely user-independent segmentation of the common carotid artery wall. Our algorithm is designed for the extraction of the intima and media layers of the distal carotid wall in ultrasound images. It is based on integrated approach consisting of common carotid artery region identification, contour initialization with threshold segmentation, intima-lumen segmentation with Snake, and media-adventitia segmentation with GVF-Snake that enables the automated tracing of the carotid walls. The acoustic impedance's difference is employed to locate common carotid artery region. Finally, the characterization of the algorithm in terms of segmentation error was evaluated with a set of 40 common carotid artery ultrasound images and compared to the segmentation traced by a trained operator. Experiments showed that a mean error lower than 1.3 pixel both on the intima and media layers was obtained, which is comparable to that obtained by means of operator dependent techniques.

关键词： image segmentation Carotid arteries Ultrasonic imaging Media Algorithm design and analysis Ultrasonic variables measurement

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