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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

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Research on human body composition prediction model based on Akaike Information Criterion and improved entropy method

Research on human body composition prediction model based on...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Bo Chen Xiue Gao Qingguo Zheng Jingfeng Wu College of Information Engineering Dalian University Dalian China College of Information Engineering Dalian University Dalian CN

ISBN: (纸本)9781509037117

The prediction model of existing human body composition based on measured bioelectricity has problems that include redundant influence factors and low prediction accuracy. To address these problems, this paper put forward a human body composition prediction model based on Akaike Information Criterion (AIC) and improved entropy method. First, combining with the AIC information principle, we selected a set of characteristic parameters from human physiological arguments, and constructed the human body composition prediction model; Second, improved entropy method was used to solve the unknown coefficients in predictive model, then worked out prediction model of human body composition; Finally, a comparative analysis experiment of the prediction model and the actual measurement data was designed, and the data were sampled by InBody770 body composition instrument. Experimental results showed that a good correlation existed between the model predictions data and the actual measurements, this study provided a theoretical basis for the model and analysis of human body composition.

关键词： Biological system modeling Predictive models Entropy Analytical models Data models Impedance biomedical measurement

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Electroencephalogram signal Analysis Based on the Improved k-nearest Neighbor Network

Electroencephalogram Signal Analysis Based on the Improved k...

引用

international congress on image and signal processing, biomedical engineering and informatics

作者： Xian Yu Chengcheng Liu Jun Wang Jiafei Dai Jin Li Fengzhen Hou Image Processing and Image Communications Key Lab Nanjing University of Posts and Telecommunications Nanjing General Hospital of Nanjing Military Command College of Physics and Information Technology Shaanxi Normal University School of Science China Pharmaceutical University

ISBN: (纸本)9781509037117

In this paper, we propose a method to analyze epileptic electroencephalogram based on time series that is transformed from improved k-nearest neighbor network. The study of complex networks has become a hot research of electroencephalogram signal. Electroencephalogram time series generated by the network keeps node information of network, so researching the time series from the network can also achieve the purpose of studying epileptic electroencephalogram. The results of this experiment show that studying power spectrum of time series from the network is more easily than the power spectrum of time series directly generated from brain data to distinguish between normal and epileptic patients. In addition, studying the clustering coefficient of improved k-nearest neighbor network is also able to distinguish between normal and patients with epilepsy. This study can provide an important reference for the study of epilepsy and clinical diagnosis.

关键词： analysis of electroencephalogram signals improved k-nearest neighbor network time series epilepsy

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image processing Technology in Broken Viscose Filament Automatic Detection System

Image Processing Technology in Broken Viscose Filament Autom...

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international congress on image and signal processing, biomedical engineering and informatics

作者： YA-LAN TAN QUN HOU HENG-WEI YU School of Physics and Information Engineering Jianghan University Wuhan China

ISBN: (纸本)9781509037117

The number of broken filament will affect the quality of viscose filament directly. It is one important quality indicator of viscose filament. This paper presents a new detection method of broken filaments based on image procession technology. The method can get lower cost and convenient usage. Firstly, by using CCD camera, we got the viscose filament images. Secondly, the images were processed in MATLAB. The numbers of white pixels (N) in the broken filaments part were calculated. Finally, the N value of images was counted and analyzed. A threshold to estimate the existence of the broken filaments was gotten. When the N is more than the threshold, we can prove these white pixels were the broken filaments. They were not caused by salt and pepper noise. In this way, we can detect the existence of broken filaments. In addition, the experiments to testify the accuracy of the threshold were done. The result shows that the method can detect the broken filament. It also turns out that the method has the potential to be used in the practical production.

关键词： image filtering Viscose filament broken filaments detection CCD camera image binarization

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Extrinsic calibration of a laser range finder and a camera based on the automatic detection of line feature

Extrinsic calibration of a laser range finder and a camera b...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhen Chen Xiaoping Yang Congxuan Zhang Shaofeng Jiang Key Laboratory of Nondestructive Testing Ministry of Education Nanchang China School of Measuring and Optical Engineering Nanchang Hangkong University Nanchang China

ISBN: (纸本)9781509037117

This paper presents an extrinsic calibration method of a camera and a laser range finder based on the automatic detection of the line feature. Firstly, a special 3D calibration target which contained four planes and five edges was projected, and then the visible image and laser data of the 3D calibration target could be obtained. Secondly, the automatic detection method of the line feature was presented, which used the linear fitting to acquire the equations of the line features detected by the Hough transform. With the obtained equations, the laser data corresponding to the line features of the 3D calibration target could be acquired by computing the crossover point of two straight-lines. Finally, the rotation matrix and translation matrix between the camera and laser range finder could be acquired with computing the linear equations provided by the laser data and the corresponding crossover point. Experimental result showed the proposed method could acquire the accurate external calibrations.

关键词： Calibration Lasers Cameras Three-dimensional displays Feature extraction Laser noise image edge detection

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Performance evaluation of greedy reconstruction algorithms in compressed sensing

Performance evaluation of greedy reconstruction algorithms i...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Hongbo Bi Chunhui Zhao Ying Liu Ning Li School of Electronic and Information Engineering Northeast Petroleum University Daqing China College of Information and Communication Engineering Harbin Engineering University Harbin China School of Electronic and Intormation Engineering Northeast Petroleum University Daqing China

ISBN: (纸本)9781509037117

Compressed sensing can decrease the cost of information acquisition, storage, processing and transmission greatly by using sampling rate far lower than that in the sampling theorem limits to realize the accurate reconstruction of sparse or compressible signal. In this paper, we introduced the basic theory of compressed sensing, and then made an in-depth study of this theory from the angle of the sparsification of signal, the structure of the measurement matrix and the reconstruction of signal. Then we derived the flowchart and realization steps of each scheme and made a comparative analysis of five kinds of classic greedy reconstruction algorithms. Simulation results show that the accuracy of the OMP algorithm for image reconstruction is the highest, and has a strong stability, however this algorithm costs too much computation time. The convergence speed of CoSaMP algorithm is faster than OMP algorithm, while the reconstruction accuracy depends on the sparsity K greatly. The convergence speed of StOMP for image reconstruction is the fastest, meanwhile the accuracy is worse than OMP algorithm. Furthermore, StOMP algorithm is adaptive, and has a better practicability. ROMP and SAMP algorithms are better than OMP algorithm in theory. However, due to the inconvenience of choosing the suitable step-size or the number of iterations in simulation process, the reconstruction performance of both two schemes are influenced seriously.

关键词： Matching pursuit algorithms Algorithm design and analysis Indexes image reconstruction Sparse matrices Approximation algorithms Compressed sensing

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Single image blind deblurring via adapting total generalized variation

Single image blind deblurring via adapting total generalized...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Wen-Ze Shao Feng Wang Qi Ge Hai-Bo Li Li-Li Huang College of Telecom. & Info. Engineering Nanjing University of Posts and Telecommunications Nanjing China School of Science Guangxi University of Science and Technology Liuzhou China

ISBN: (纸本)9781509037117

This paper introduces a fast blind deconvolution strategy for image deblurring by modifying a recent natural image model, i.e., the total generalized variation (TGV), which aims at reconstructing an image with higher-order smoothness as well as sharp edges. But, when it turns to the blind issue, as demonstrated either empirically or theoretically by a few previous blind deblurring works, natural image models including TGV are more often than not inclined to trivial solutions, e.g., the delta blur kernel and the input blurred images. Inspired by the discovery, a simple, yet effective modifying strategy is applied to the second-order TGV, leading to a novel ℓ 0 -ℓ 1 -norm-based image regularization adaptable to the blind deblurring problem. Then, a numerical algorithm is deduced with O(NlogN) complexity, via borrowing ideas of the operator splitting method, the augmented Lagrangian, and also the fast Fourier transform (FFT). Experimental results on both synthetic and real color blurred images demonstrate the superiority or comparable performance of the new approach to state-of-the-art ones, in terms of deblurring accuracy and efficiency.

关键词： Kernel Estimation image restoration Complexity theory Deconvolution Adaptation models image edge detection

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Retinal image automatic registration based on local bifurcation structure

Retinal image automatic registration based on local bifurcat...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Kun Zhang Encai Zhang Jichun Li Guannan Chen Key Laboratory of OptoElectonic Science and Technology for Medicine Ministry of Education Fujian Normal University Fuzhou China Department of Network and Communication Engineering Fujian Normal University Fuzhou China

ISBN: (纸本)9781509037117

Retinal images can be used for helping ophthalmologist to diagnose the eye diseases, and glaucoma, hypertension, coronary heart diseases and so on, so it's very important. The most important content of this article is a new structural feature for retinal registration. There are many methods of retinal image registration; some are also used by this time. Lots of methods used the main bifurcation points and angles. This method is well and effective, but there are some problems, for example, the angles about bifurcation maybe repeat, so in two images, the bifurcation registration may be failed. On the basis of this, in this paper we proposed a structure-matching registration method. The bifurcation structures are consists of a main bifurcation point and its three connected branches. The each numerical value of bifurcation is composed of the bifurcation angles and its three lengths by normalized. On the other hand the bifurcation structure will be invariant against rotation, translation and scaling. By this method, we can reduce the matching error caused by repeated. This method could be used alone, also could be used with other methods.

关键词： Bifurcation Retina image registration Feature extraction Diseases biomedical imaging Periodic structures

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Wrist pulse recognition based on multi-fractal spectrum

Wrist pulse recognition based on multi-fractal spectrum

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Nan Zhang Guangqin Hu Xinfeng Zhang Wenming Yu Zheng Yang Mengru Guo Beijing University of Technology Beijing CN College of Electronic and Control Engineering Beijing University of Technology Beijing China Beijing Laboratory For Urban Mass Transit Beijing China Engineering Research Center of Digital Community Ministry of Education Beijing China Beijing University of Chinese Medicine Beijing China Hebei University of Science & Technology Shijiazhuang China

ISBN: (纸本)9781509037117

Pulse diagnosis is an important part of the theoretical system of Traditional Chinese Medicine. In this paper we propose a new and an efficient framework to recognize pulse signal in nonlinear angle. Firstly the EEMD (ensemble empirical mode decomposition) method is used to filter out baseline drifting noise, and the result is proved to be effective. Then the MFDFA(multi-fractal detrended fluctuation analysis) method is used to get Hurst index, Renyi index and multi-fractal spectrum. Hurst index is related with the long-range correlations, Renyi index is related with the multi-fractal characteristics, and multi-fractal spectrum contains Δa and Δf characteristics. Finally, four kinds of pulse signals are recognized by PSO-SVM after extract multi-fractal spectrum feature. Experiment results demonstrate the effectiveness of our proposed method.

关键词： Fractals Time series analysis Feature extraction Indexes Fluctuations Time-frequency analysis Low-pass filters

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A Digital Audio Watermarking Algorithm Based On Independent Component Analysis

A Digital Audio Watermarking Algorithm Based On Independent ...

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international congress on image and signal processing, biomedical engineering and informatics

作者： Qian Cai Xianghong Tang School of Communication Engineering Hangzhou Dianzi University Zhejiang China School of Information Engineering Hangzhou Dianzi University Zhejiang China

ISBN: (纸本)9781509037117

This paper proposes a digital audio watermarking algorithm based on discrete wavelet transform (DWT), singular value decomposition (SVD) and independent component analysis (ICA). Firstly, it preprocesses original audio to select the appropriate fragments to embed watermark when embedding a watermark. It uses three level wavelet transform to the original audio and singular value decomposition to the approximate components. Then it uses a random method to complete mixing to improve watermark's imperceptibility and robustness. When extracting a watermark, it uses wavelet transform and singular value decomposition to the watermarked audio signal. Then it uses fixed-point algorithm (Fast-ICA) method which based on negative entropy maximization to achieve blind watermark detection. The simulation results show that the algorithm has strong robustness and imperceptibility.

关键词： Adaptive watermark Discrete wavelet transform Singular value decomposition Independent component analysis Blind watermark detection

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Model and metric choice of image retrieval system based on deep learning

Model and metric choice of image retrieval system based on d...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Lei Wang Xili Wang Center of Network Shangluo University Shangluo China School of Computer Science Shaanxi Normal University Xi'an China

ISBN: (纸本)9781509037117

In the era of big data, Content-Based image Retrieval combined with deep learning technology gradually becomes the mainstream. This method can overcome some drawbacks of traditional CBIR, but at the same time there are still some problems to be solved, such as: The extracted feature dimension (generally more than 2000) is higher, which is not beneficial for efficient data storage and fast real-time query on a large scale; And the measurement method for feature matching is difficult to be determined, since the typical method based on distance is designed in the low dimension, but in high dimensional space curse of dimensionality can make those former methods may be no longer suitable. In this paper we discuss a fast efficient CBIR to improve the performace of image retrieval system, through contrasting different model and metric choices. Contrast experiments show that 4 kinds of distances (namely Euclidean Distance, Minkowski Distance, Cosine Distance, Pearson Correlation Distance) is more suitable for processing the similarity measurement on high-dimensional feature, and 5 kinds of models ( namely vgg-m-128, vgg-m-1024, vgg-m-2048, vgg-verydeep-16, vgg-verydeep-19) have higher average query precision for image retrieval task.

关键词： image retrieval Correlation Feature extraction Euclidean distance Biological neural networks Machine learning

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