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2013 International Conference on Information,Business and Education Technology(ICIBET 2013)

作者： Ruijun Chang Liu Yang Qiuping Chen Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

ISBN: (纸本)9781629932101

The quality of sleep has a great relationship with health. The result of sleep stage classification is an important indicator to measure the quality of sleep. It was found that the symbolic transfer entropy about the α wave of the wake and the first stage of non-rapid eye movement sleep reflect on the changes of sleep stage. And it was confirmed by T test and multisamples experiments. The symbolic transfer entropy can apply into automatic sleep stage classification. By Multi-parameter analysis it could achieve a higher accuracy of sleep stage classification.

关键词： EEG symbolic transfer entropy sleep stage classification, α wave

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Pathological Electrocardiogram Analysis based on Symbolic Relative Entropy

Pathological Electrocardiogram Analysis based on Symbolic Re...

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2013 International Conference on Bio-Medical Materials and Engineering(ICBME 2013)

作者： Jiakai Qiu Xiaoliang Huang Suyi Chang Yunxia Wang Jun Wang Image Processing and Image Communications Key Lab College of Geo & Bio InformationNanjing Univ of Posts & Telecomm

In this paper, symbolic relative entropy was used to analyze normal electrocardiogram(ECG), the ECG taken from patient with congestive heart failure(CHF) and Atrial fibrillation(AF) Statistical testing showed that the symbolic relative entropy of normal ECG was distinctly higher than that of CHF while the symbolic relative entropy of CHF was distinctly higher than that of AF It discoved that symbolic relative entropy can be used to analyze the different pathological ECG which could be used to assisted clinical diagnosis

关键词： Symbolic the Relative Entropy Electrocardiogram

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A compressive sensing based mobile video communication system

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Sensors and Transducers 2013年第6期153卷 186-191页

作者： Wu, Minghu Li, Ran Zhou, Shangli School of Electrical and Electronic Engineering Hubei University of Technology Wu'han 430068 China Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

A compressive sensing (CS) based mobile video communication system is proposed to meet the requirement that video service needs low-complexity video encoder in the mobile internet. In this system, the mobile client uses CS based video encoder having low computational complexity and power, and then its output bit-stream is decoded using CS recovery algorithm in the fixed base station or network server. The decoded video signal is transformed again as bits by the traditional H.264/MPEG video encoder, and the central base station transmits them to mobile clients so as to realizing low-complexity video decoding. The simulation experiments show that the proposed CS based mobile video communication system has the better rate-distortion performance, and can ensure high quality video reconstruction at low measurement rates. © 2013 IFSA.

关键词： Compressed sensing

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image representation and recognition based on directed complex network model

Image representation and recognition based on directed compl...

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8th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2013

作者： Chen, Ying Tang, Jin Luo, Bin School of Computer Science and Technology Anhui University Hefei230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei230039 China

ISBN: (纸本)9783642375019

image structure representation is a vital technique in the image recognition. A novel image representation and recognition method based on directed complex network is proposed in this paper. Firstly, the key points are extracted from an image as the nodes to construct an initial complete undirected complex network. Then, the k-nearest neighbor evolution method is designed to form a series of directed networks. At last, the feature descriptor of the image is constructed by concatenating the structure features of each directed network to finally achieve image recognition. Experimental results demonstrate that the proposed method outperforms the traditional methods in image recognition and can describe the structure of images more effectively. © Springer-Verlag Berlin Heidelberg 2013.

关键词： image recognition

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Evaluation of bodily-kinesthetic intelligence based on computer contextual method

Evaluation of bodily-kinesthetic intelligence based on compu...

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2013 International Conference on Sport Science and Computer Science (CCCS 2013)

作者： Qi Xia Wei Wang Jun Wang College of Education Science Nanjing Normal University Key Laboratory of Image Processing and Image Communication of Jiangsu Province Nanjing University of Posts and Telecommunications

There are two main types of tests to assess one's bodily-kinesthetic intelligence,which are writing tests and scenario ***,these two methods are subjective and time-consuming and not suitable for large-scale *** paper proposed a new assess method to assess bodily-kinesthetic intelligence based on the writing intelligence test *** method is designed with the computer virtual reality *** result shows the method can get better reliability and *** the evaluation process is easier to realize.

关键词： bodily-kinesthetic intelligence multiple intelligence computer contextual method

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A probability-based object tracking method

A probability-based object tracking method

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Song, Xu Li, Guoqiang Li, Ying Zhang, Yanning Shaanxi Province Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an 710129 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Here we take advantage of the signal recovery power of Compressive Sensing (CS) to significantly reduce the computational complexity brought by the high-dimension image data, then an effective and efficient low-dimensional subspace representation of the object is computing by applying Principal Component Analysis (PCA) to a collection of object observations which are low-dimensional vectors derived from CS. An incremental PCA algorithm is used to update this subspace model for characterizing the object appearance changes. Meanwhile, two distances derived from Probabilistic Principal Component Analysis (PPCA): distance from feature space (DFFS) and distance in feature space (DIFS), are used to describe visual similarity between the learned subspace representation model and candidate targets. Comparing with the traditional used reconstruction error, the sum of two distances: DFFS + DIFS, is more accurate and more robust to noises and partial occlusions. Numerous experiment demonstrate that subspace representation model can handle the situation that target objects experience pose changes, scale changes, significant illumination variation, partial occlusions and so on. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Compressed sensing

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An improved method in change detection of multitemporal remote sensing image

An improved method in change detection of multitemporal remo...

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4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Liao, Fangshun Yu, Sufen Li, Ying Zhang, Yanning Shaanxi Provincial Key Lab. of Speech and Image Information Processing Northwestern Polytechnical University Xi'an Shaanxi 710072 China Science and Technology on Electro-optic Control Laboratory Louyang 471009 China

ISBN: (纸本)9783642420566

Traditional Markov random Field (MRF) methods assume that neighboring pixels tend to have the same label. However, this assumption is always inconsistent with the actual situation and affects the resultant accuracy of the algorithm. To overcome this, we propose an object-based Markov Random Field (OMRF) model and a change detection method based on OMRF model. The OMRF model assumes that pixels within same object are in the same class. First, we generate the difference image from multi-temporal remote sensing images. Second, Mean Shift is applied to extract objects from difference image. Finally, change detection map is generated by iterative algorithm. The experimental results show that the algorithm can effectively improve the detection accuracy of the algorithm on real remote sensing datasets. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Change detection

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Video summarization by robust low-rank subspace segmentation

Video summarization by robust low-rank subspace segmentation

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8th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2013

作者： Tu, Zhengzheng Sun, Dengdi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei230039 China School of Computer Science and Technology Anhui University Hefei230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei230039 China

ISBN: (纸本)9783642375019

Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper. Firstly, video frames are represented as multi-dimensional vectors, and then embedded into a group of affine subspaces using low-rank representation according to the content similarity of the frames in the same subspace. Secondly, a series of subspaces are segmented based on the Normalized Cuts algorithm. The video summary is finally generated by choosing key frames from the significant subspaces and ranking these key frames in temporal order. The experimental results demonstrate that the proposed summarization algorithm can produce crucial key frames and effectively reduce the visual content redundancy in summary comparing with the conventional approaches. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Vectors

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SUBJECTIVE AND OBJECTIVE QUALITY ASSESSMENT FOR imageS WITH CONTRAST CHANGE

SUBJECTIVE AND OBJECTIVE QUALITY ASSESSMENT FOR IMAGES WITH ...

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IEEE International Conference on image processing

作者： Ke Gu Guangtao Zhai Xiaokang Yang Wenjun Zhang Min Liu Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai Key Laboratory of Digital Media Processing and Transmissions

ISBN: (纸本)9781479923427

It is widely known that, for most natural images, appropriate contrast enhancement can usually lead to improved subjective quality. Despite of its importance to image processing, contrast change has largely been overlooked in the current research of image quality assessment (IQA). To fill this void, in this paper we first report a new and dedicated contrast-changed image database (CID2013). The CID2013 database is composed of four hundred contrast-changed images of fifteen original natural images and the mean opinion scores (MOSs) recorded from twenty-two inexperienced viewers. We then proposed a novel reduced-reference image quality metric for contrast-changed images (RIQMC) using entropies and order statistics of the image histograms. Experimental results on the CID2013, TID2008, and CSIQ databases demonstrate that the proposed RIQMC metric outperforms some mainstream image quality assessment methods.

关键词： Contrast-changed image database Mean opinion score (MOS) image quality assessment (IQA) Entropy Order statistics images entropy Quality assessment image quality Musci contrast enhancement Micturition current research image histogram

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A local elitism based membrane evolutionary algorithm for point pattern matching

A local elitism based membrane evolutionary algorithm for po...

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8th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2013

作者： Ding, Zhuanlian Tang, Jin Zhang, Xingyi Luo, Bin School of Computer Science and Technology Anhui University HefeiAnhui230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province HefeiAnhui230039 China

ISBN: (纸本)9783642375019

Point pattern matching is a fundamental problem in computer vision and pattern recognition. Membrane computing is an emergent branch of bio-inspired computing, which provides a novel idea to solve computationally hard problems. In this paper, a new point pattern matching algorithm with local elitism strategy is proposed based on membrane computing models. Local elitism strategy is used to keep good correspondences of point pattern matching found during the search, so the matching rate and the convergence speed are improved. Five heuristic mutation rules are introduced to avoid the local optimum. Experiment results on both synthetic data and real world data illustrate that the proposed algorithm is of higher matching rate and better stability. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Membranes

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