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检索条件"机构=Vienna University of Technology Pattern Recognition and Image Processing"

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Signal processing Based for Fetal Electrocardiogram Extraction

Signal Processing Based for Fetal Electrocardiogram Extracti...

引用

International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Saman Sargolzaei Karim Faez Arman Sargolzaei Image Processing and Pattern Recognition Laboratory Department of Electrical Engineering Amirkabir University of Technology슠 Tehran Iran Department of Electrical Engineering University of Sadjad Mashhad Iran

In this paper, we describe four important indirect methods which be used to extract the fetal Electrocardiogram (FECG) signal from an ECG recorded on the mother's abdomen. These methods include the following ones: singular value decomposition (SVD) method, independent component analysis (ICA) method, wavelet based methods and adaptive filtering method. The mentioned methods use signal processing techniques for extracting FECG from abdominal electrocardiogram (AECG). We have explained advantages and disadvantages of each method. The methods have also applied on both synthetic and real ECG signals. Efficiencies of the methods compared together based on three important criterions and results are stated and best method based on three criterions is selected.

关键词： Signal processing Abdomen Fetus Electrocardiography Electrodes Independent component analysis Heart Low-frequency noise Noise level Biomedical signal processing

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The Application of A Novel Target Region Extraction Model Based on Object-Accumulated Visual Attention Mechanism

The Application of A Novel Target Region Extraction Model Ba...

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International Conference on Natural Computation (ICNC)

作者： Jie Xiao Chao Cai Mingyue Ding Chengping Zhou Institute of Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

Combining bottom-up and top-down attention influences, a novel region extraction model which based on object-accumulated visual attention mechanism is proposed in this paper. Compared with early research, the new approach brings in prior information at the proper time, updates scan path dynamically, needs less computational resources and reduces the probability to direct the attention to a less-meaning area. The application to search an airport target in remote sensing image was provided, through which the novel mechanism that how visual attention chose the area was described. Compared with another two region extraction models, experimental results confirm the effectiveness of the approach proposed in this paper.

关键词： Data mining Object detection Computer applications Chaos pattern recognition Artificial intelligence Laboratories image processing Intelligent control Airports

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Extraction of complex wavelet features for iris recognition

Extraction of complex wavelet features for iris recognition

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International Conference on pattern recognition

作者： Xiaofu He Pengfei Shi Department of Computer Science and Technology East China Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Shandong Jiaotong University Shanghai China

ISBN: (纸本)9781424421749

This paper presents a new feature extraction method for iris recognition. Since two dimensional complex wavelet transform (2D-CWT) does not only keep wavelet transformpsilas properties of multiresolution decomposition analysis and perfect reconstruction, but also adds its new merits: approximate shift invariance, good directional selectivity for 2-D image, and limited redundancy, which are useful for iris feature extraction. So, a set of high frequency 2D-CWT coefficients are selected as features for iris recognition. The phase information of the coefficients is used for feature encoding and Hamming distance is adopted for classification. Experimental results show that the proposed algorithm can get good recognition rate.

关键词： Iris recognition Feature extraction Wavelet analysis Wavelet transforms image resolution image analysis image reconstruction Two dimensional displays Frequency Encoding

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Extracting key postures in a human action video sequence

Extracting key postures in a human action video sequence

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IEEE Workshop on Multimedia Signal processing

作者： Yan Chen Qiang Wu Xiangjian He Chunhua Du Jie Yang Falculty of Information Technology Sydney University of Technology Broadway NSW Australia Falculty of Information Technology University of Technology-Sydney Broadway NSW Australia Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424422944

Human key posture extraction from videos will benefit video storage, video retrieval, human action recognition, human behaviour understanding and so on. This paper presents an approach to select key postures from human action sequences using 2D information. There are two steps in the proposed method. Information measurement which is a kind of global feature of a frame is used to roughly find key posture candidates. Then, a body skeleton feature which is a kind of local feature is applied to select final key postures from the candidates obtained in the first step. The experiments show that the proposed method is efficient.

关键词： Humans Data mining Databases Equations Shape Conferences Distance measurement

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Multi-view ear recognition based on B-Spline pose manifold construction

Multi-view ear recognition based on B-Spline pose manifold c...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Zhiyuan Zhang Heng Liu Harbin Institute of Technology (HIT)Shenzhen Graduate School Bio-computing Research Center Shenzhen China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

In this work, multi-view ear recognition problems are examined in detail. A new multi-view ear recognition approach based on B-Spline pose manifold construction in discriminative projection space which is formed by null kernel discriminant analysis (NKDA) feature extraction is presented. Many experiments and comparisons are provided to show the effectiveness of our multi-view ear recognition approach.

关键词： Ear Manifolds Spline Feature extraction Principal component analysis Kernel Construction industry

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Three Dimensional Palmprint recognition using Structured Light Imaging

Three Dimensional Palmprint Recognition using Structured Lig...

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IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS)

作者： David Zhang Guangming Lu Wei Li Lei Zhang Nan Luo Department of Computing Hong Kong Polytechnic University Hong Kong China Shenzhen Graduate School Harbin Institute of Technology Shenzhen China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Palmprint is one of the most unique and stable biometric characteristics. Although 2D palmprint recognition can achieve high accuracy, the 2D palmprint images can be easily counterfeited and much 3D depth information is lost in the imaging process. This paper presents a new approach, 3D palmprint recognition, to exploit the 3D structural information of the palm surface. The structured-light imaging is used to acquire the 3D palmprint data, from which the features of Mean Curvature, Gauss Curvature and Surface Type (ST) are extracted. A fast feature matching and score level fusion strategy are then used to classify the input 3D palmprint data. With the established 3D palmprint database, a series of verification and identification experiments are conducted and the results show that 3D palmprint technique can achieve high recognition rate while having high anti-counterfeiting capability.

关键词： image recognition Biometrics Feature extraction Authentication Data mining Counterfeiting image databases Spatial databases Ear Clouds

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Modeling multisource remote sensing image classifier based on the MDL principle: Theoretical aspects

Modeling multisource remote sensing image classifier based o...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qian Yin Ping Guo Zhi-Yong Yuan Zu-Kuan Wei Wen-Yi Zeng Image Processing & Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science Wuhan University of China Wuhan China School of Comp. Science & Engr. University of Electronic Science and Technology Chengdu China

A theoretical study for modeling technique of the remote sensing image classification based on the minimum description length (MDL) principle is presented in the paper. According to the MDL principle, modeling problem is an optimization procedure to find the shortest expected code length. Kullback-Leibler (KL) divergence is adopted as the system cost function to measure expected codelength, and the codelength will be the model we desired. The advantage of using the MDL principle to build appropriate model is analyzed theoretically, model optimization technique also is described.

关键词： Data models Remote sensing Mathematical model Classification algorithms Computational modeling Equations Artificial neural networks

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Needle Segmentation Using 3D Quick Randomized Hough Transform

Needle Segmentation Using 3D Quick Randomized Hough Transfor...

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International Workshop on Intelligent Networks and Intelligent Systems (ICINIS)

作者： Wu Qiu Mingyue Ding Ming Yuchi Institute for Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China Department of Biomedical Engineering School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 3D quick randomized Hough transform (3DGHT), which is based on the 3D randomized Hough transform and coarse-fine searching strategy. We tested it with water phantom. The results show that our algorithm works well in 3D US images with angular deviation less than 1 degree and position deviation less than 1 mm, and the computational time of segmentation with 35 MB data is within 1s.

关键词： Needles image segmentation Electrodes Ultrasonic imaging Intelligent networks Artificial intelligence Educational technology Hemorrhaging Imaging phantoms Radio frequency

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Dim small targets fusion detection in infrared image

Dim small targets fusion detection in infrared image

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Yu-Qiu Sun Yu Zheng Jin-Wen Tian Jian Liu School of Information and Mathematics Yangtze University Jingzhou China State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China State Education Commission Key Laboratory for Image Processing and Intelligent Control Department of Electronic Information and Enginery of Huazhong University of Science and Technology Wuhan China

To infrared images, the contrast of target and background is low, dim small targets have no concrete shapes and their textures cannot be reliable predicted. The paper puts forward a novel algorithm to fuse mid-wave and long-wave infrared images and detect targets. Firstly, the source images are decomposed by wavelet transformation. In usual, targets in infrared images are man-made, and their fractal dimension is different comparing with natural background. In wavelet transformation domain high-frequency part, we calculate local fractal dimension and set up fusion rule to merge corresponding sub-images of two matching source images. In low-frequency, we extract local maximum gray level to fuse them. Then reconstruct image by wavelet inverse transformation and obtain fused result image. In fusion results, the contrast between targets and background has obvious changes. And targets can be detected using contrast threshold. The experimental results show that the method proposed in this paper using wavelet transformation fractal dimension to fuse dual band infrared images, and then detect targets is better than using mid-wave or long -wave infrared images detect targets alone.

关键词： Fractals Wavelet transforms Pixel Object detection Fuses Approximation methods Manganese

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A novel video scrambling algorithm based on the generalized fibonacci tranformations

A novel video scrambling algorithm based on the generalized ...

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IASTED International Conference on Communication Systems, Networks, and Applications, CSNA 2007

作者： Jiancheng, Zou Zhipeng, Chen Institute of Image Processing and Pattern Recognition North China University of Technology China

ISBN: (纸本)9780889867024

A novel video scrambling algorithm based on generalized Fibonacci numbers is given in this paper. The experiment results show that the algorithm has better robust than the traditional video scrambling algorithm. Based on the property of uniformity of the corresponding Fibonacci transformation, the suggested method has the following advantages: (1) Encoding and decoding are very simple and they can be applied in real-time situations. (2) The algorithm can endure severe attacks such as extreme noise levels, very high loss in its data or data packets. (3) The algorithm is independent on any video format or encode mode.

关键词： Security of data

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