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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Chen, Zhong Deng, He Wang, Guoyou Intelligence Control Insititute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Multi-Spectral Information Processing State Key Laboratory Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

image mosaic technology is an important research field of image processing and a research focus on the computer vision and computer graphics. The traditional method is to select the feature points by manual selection method, which faces the problem of low reliability and efficiency in the batch of the image mosaic. The SIFT features have many properties that make them suitable for matching differing images of an object or scene. But the computation amount and the computation complexity are so great, which restricts the further real time application. So an automatic remote sensing image mosaic algorithm based on modified SIFT feature is presented in this paper to solve these problems. The method presented in this paper consisted of three steps: noise removal, modified SIFT feature registration and automatic mosaic. The test results show the modified mosaic algorithm based on the SIFT feature can improve the matching accuracy and reduce the computation times. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Computer graphics

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An improved method of identification based on thermal palm vein image 1

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19th International Conference on Neural Information processing, ICONIP 2012

作者： Wang, Ran Wang, Guoyou Chen, Zhong Liu, Jianguo Shi, Yu National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 1037 Luoyu Road Hongshan District 430074 Wuhan Hubei Province China

ISBN: (数字)9783642344817

ISBN: (纸本)9783642344800

Biological characteristics based on face, fingerprint and iris images have been extensively studied and used for the identification in the past few decades. As a new-born method, thermal palm vein pattern is gathering more and more attention all over the world. An improved method of identification based on thermal palm vein image is presented in the paper. Five steps are needed to have a person verified: 1) acquisition of infrared palm vein image;2) detection of ROI (region of interest);3) enhancement of the palm vein image;4) features extraction of the palm vein patterns;5) matching the features between the real palm vein and sample data. Experiments have been carried out on 178 different images and 176 images of them are correctly recognized with two in failure. Experiments show the detection rate is satisfied. © 2012 Springer-Verlag.

关键词： image enhancement

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A general framework for machine vision: hierarchical token grouping

A general framework for machine vision: hierarchical token g...

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International Symposium on Speech, image processing and Neural Networks

作者： Qian Huang Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East Lansing MI USA

ISBN: (纸本)078031865X

While the view of constructive and hierarchical vision prevails, the issues of cooperation and competition among individual modules become crucial. These issues are directly related to one of the most important aspects in computer vision research: integration. A major source of difficulty in developing a consistent and systematic integration formalism is the heterogeneity existing in modules, in information, and in knowledge. The author exploits, using the central theme of grouping, the homogeneous characteristics in vision problem solving and proposes a general framework, called hierarchical token grouping, that facilitates vision problem solving by providing a consistent and systematic environment for integrating modules, cues, and knowledge, all in a globally coherent mechanism.< >

关键词： Machine vision Problem-solving Computer vision Organizing pattern recognition image processing Laboratories Computer science Gratings Humans

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A Fall Detection System Based on a Thermopile Imaging Array and a Back Projection Algorithm

A Fall Detection System Based on a Thermopile Imaging Array ...

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IEEE International Conference on Electro-Information Technology

作者： Lei Yu Han Chen Hantao He Hong Nie Xuping Zhai Bangshu Xiong Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China University of Northern Iowa Iowa USA Shanghai University Shanghai China

ISBN: (数字)9781728153179

ISBN: (纸本)9781728153186

In this paper, a fall detection system consisting of a thermopile imaging array with 80*64 pixels and a Raspberry Pi 3 has been developed. First, the thermal images captured by the hardware system are processed to eliminate fixed interferences and identify the human body. Then, the real height of the human body is estimated from the original height in the thermal images. Finally, after smoothing the fluctuation of the real height, fall events are detected according to the relative variations of the smoothed height. Our experiments show that the newly developed system and image processing algorithm can achieve much better performance on fall detection than other systems based on infrared sensors or sensor arrays.

关键词： Imaging Sensor arrays Senior citizens Projection algorithms Infrared sensors image resolution

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One-shot distributed algorithm for PCA with RBF kernels

arXiv

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arXiv 2020年

作者： He, Fan Lv, Kexin Yang, Jie Huang, Xiaolin The Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China The MOE Key Laboratory of System Control and Information Processing 800 Dongchuan Road Shanghai200240 China

This letter proposes a one-shot algorithm for feature-distributed kernel PCA. Our algorithm is inspired by the dual relationship between sample-distributed and feature-distributed scenario. This interesting relationship makes it possible to establish distributed kernel PCA for feature-distributed cases from ideas in distributed PCA in sample-distributed scenario. In theoretical part, we analyze the approximation error for both linear and RBF kernels. The result suggests that when eigenvalues decay fast, the proposed algorithm gives high quality results with low communication cost. This result is also verified by numerical experiments, showing the effectiveness of our algorithm in practice. Copyright © 2020, The Authors. All rights reserved.

关键词： Principal component analysis

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A new approach to finite wordlength coefficient fir digital filter design using the branch and bound technique 10

A new approach to finite wordlength coefficient fir digital ...

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2000 10th European Signal processing Conference, EUSIPCO 2000

作者： Belbachir, A.N. Boulerial, B. Belbachir, M.F. Signal and System Laboratory Electronic Institute U.S.T.O. B.P. 1505 El Mnouer Oran Algeria Vienna University of Technology Pattern Recognition and Image Processing Group Favritenstr. 9/1832 ViennaA-1040 Austria

ISBN: (纸本)9789521504433

It has been shown that the branch and bound technique is effective for the design of finite wordlength optimal digital filters. This technique is however expensive in computing time. In this paper, we present a robust branch and bound branching strategy named Sequential and Progressive Search, improving the design of filters on a large wordlength processor in a reasonable computing cost. The details of the algorithm and many examples are given and compared to the other methods. © 2000 EUSIPCO.

关键词： Digital filters

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Generalized stochastic tube model: Tracking 3D blood vessels in MR images 12

Generalized stochastic tube model: Tracking 3D blood vessels...

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12th IAPR International Conference on pattern recognition - Conference B: pattern recognition and Neural Networks, ICPR 1994

作者： Huang, Qian Stockman, George C. IBM Research Division Almaden Research Center 650 Harry Road San JoseCA95120-6099 United States Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East LansingMI48824 United States

ISBN: (纸本)0818662700

This paper addresses the issue of tracking tubular objects, particularly blood vessels from MR images. A model-based approach is adopted. The generalized stochastic tube (GST) model is developed which is an extension of our previously proposed Generalized Tube (GT) model. Transitions among adjacent tubes are explicitly parameterized. Integrated with a bivariate Gaussian density function adopted to model the blood flow within cross sections, the GST model is applied to tracking blood vessels in MRA volumetric data. Experimental results on both synthetic data with different degrees of Gaussian noise and real MRA data demonstrated that simultaneously utilizing both models yields robust performance under noisy conditions. © 1994 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Blood vessels

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Integrating Segmentation and Classification Accuracy for Accuracy Assessment in Object-based image Analysis

Integrating Segmentation and Classification Accuracy for Acc...

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International Conference on Audio, Language and image processing

作者： Nan Li Hong Huo Tao Fang Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education Institute of Image Processing and PatternRecognition Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781467301732

An accuracy assessment method that integrates segmentation and classification accuracy is proposed to meet the requirements of object-based image analysis. Segmentation errors are measured by establishing the relationship between pixels and their corresponding segments according to the overlaps of segments and reference polygons. Then, two improved confusion matrices that take the segmentation errors into consideration are used: one for pixel-level classification results, and the other for object-level classification results. A final accuracy assessment combines the statistics of these two confusion matrices. The proposed method can be applied to segmentation scale selection in the hierarchical interpretation system. An experiment on a SPOT5 image demonstrates the effectiveness of this method for segmentation scale selection, which can guide the fusion of objects of different scales to obtain a higher accuracy.

关键词： segmentation image analysis Segmentation object orientation confusion matrix pixel

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An Improved Embedding Model for Zero-Shot Classification based on Attention Mechanism

An Improved Embedding Model for Zero-Shot Classification bas...

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Zongfeng Wu Qishen Li Xiao Yu Xu Peng School of Information Engineering Nanchang Hangkong University Nanchang Jiangxi China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Jiangxi China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

It is well-known that the auxiliary information plays a key role in zero-shot classification. However, most of the existing popular methods do not make effective use of auxiliary information. To address this issue, we propose an improved embedding model for zero-shot classification based on attention mechanism, called EMAM. In the proposed EMAM, we first add an attention mechanism to effectively extract the key information of auxiliary information in zero-shot classification. Then optimizes the objective function to improve the recognition rate of this model. Finally the experimental comparison is implemented on the standard zero-shot learning datasets. The experimental results demonstrate that our proposed EMAM not only verifies its validity, but also achieves good results.

关键词： Automation Conferences Linear programming Data mining Information technology Standards

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Model-based automatic recognition of blood vessels from MR images and its 3D visualization

Model-based automatic recognition of blood vessels from MR i...

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The 1994 1st IEEE International Conference on image processing

作者： Huang, Qian Stockman, G.C. IBM Research Division Almaden Research Center 650 Harry Road San JoseCA95120-6099 United States Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East LansingMI48824 United States

A model-based approach is used for recognizing arterial blood vessels from MRA volumetric data. The modeling includes (1) a generalized stochastic tube model characterizing the structural properties of the vessels, and (2) a bivariate Gaussian function, modeling the expected cross sectional blood flow. This integrated model renders the recognition problem as a parameter estimation problem which is subsequently solved in a hierarchical fashion. Due to the descriptive representation for objects, a new visualization scheme for blood vessels is proposed that allows the observation of the blood flow of each cross section along a recognized vessel. Some experimental results from both synthetic data and real MRA volumes are given. The visualization of interior blood flow patterns for some vessels are also shown. © 1994 IEEE.

关键词： Blood vessels

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