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arXiv 2022年

作者： He, Fan Yang, Ruikai Shi, Lei Huang, Xiaolin Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University The MOE Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Key Laboratory for Contemporary Applied Mathematics China School of Mathematical Sciences Fudan University Shanghai200240 China

This paper studies kernel PCA in a decentralized setting, where data are distributively observed with full features in local nodes and a fusion center is prohibited. Compared with linear PCA, the use of kernel brings challenges to the design of decentralized consensus optimization: the local projection directions are data-dependent. As a result, the consensus constraint in distributed linear PCA is no longer valid. To overcome this problem, we propose a projection consensus constraint and obtain an effective decentralized consensus framework, where local solutions are expected to be the projection of the global solution on the column space of local dataset. We also derive a fully non-parametric, fast and convergent algorithm based on alternative direction method of multiplier, of which each iteration is analytic and communication-efficient. Experiments on a truly parallel architecture are conducted on real-world data, showing that the proposed decentralized algorithm is effective to utilize information of other nodes and takes great advantages in running time over the central kernel PCA. Copyright © 2022, The Authors. All rights reserved.

关键词： Principal component analysis

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Support value based fusing images with different focuses

Support value based fusing images with different focuses

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Sheng Zheng Yu-Qiu Sun Jin-Wen Tian Jian Liu State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China China Three Gorges University Yichang China

Many vision-related processing tasks, including edge detection and image segmentation, can be performed more easily when all objects in the scene are in good focus. However, in practice, this may not be always feasible as optical lenses, especially those with long focal lengths, only have a limited depth of field. One classical approach to recover an everywhere-in-focus image is to use Laplacian pyramid image fusion. First, several source images with different focuses of the same scene are taken and decomposed into the low/high-frequency components image sequences. Within these decompositions, the high-frequency components image sequences with the largest magnitude are selected at each pixel location. Finally, the fused image can be recovered from the decomposed components image sequences. In the support vector machine (SVM), the pixels with larger support values have a physical meaning in the sense that they reveal relative more importance of the data points for contributing to the SVM model. In this paper, we use Laplacian pyramid for the multi resolution decomposition, and then replace the traditional salient features by support values of the mapped least squares (LS)-SVM for fusing image. Experimental results illustrate that the proposed method outperforms the traditional approach.

关键词： Focusing image sequences Support vector machines Layout Laplace equations image edge detection image segmentation Optical sensors Lenses image fusion

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Automatic Monitoring of Driver's Physiological Parameters Based on Microarray Camera

Automatic Monitoring of Driver's Physiological Parameters Ba...

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IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS)

作者： Jiancheng Zou Zhengzheng Li Peizhou Yan Institute of Image Processing and Pattern Recognition North China University of Technology Beijing Key Laboratory of Urban Rod Traffic Intelligent Control Technology North China University of Technology Shijingshan District Beijing China

Driver's physical and mental states are very important factors affecting the driving states. Traffic accidents are occurred by accompanying abnormal physiological parameters. So how to monitor automatically driver's physiological parameters is an important problem. A real-time driver's physiological parameters monitoring method based on microarray camera is proposed in this paper. Firstly, we use a microarray camera to acquire videos in real time without contact. Secondly, the videos are registered and fused into a high quality video. Thirdly, deep learning framework is used to capture driver's facial data quickly. Then based on the principle of imaging photoplethysmography (IPPG) algorithm, physiological parameters such as heart rate (HR) and oxygen saturation (SpO 2 ) are monitored in real time. Results of expression analysis can further support the physiological parameters monitoring results. The experimental results show that the method proposed in this paper can monitor the physiological parameters of drivers in real time and accurately, and it is hopeful to play an active role in improving traffic safety.

关键词： Biomedical monitoring Monitoring Cameras Videos Heart rate Real-time systems

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Epileptic EEG Signal Classification with ANFIS Based on Harmony Search Method

Epileptic EEG Signal Classification with ANFIS Based on Harm...

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International Conference on Computational Intelligence and Security

作者： Jing Wang X.Z. Gao Jarno M.A. Tanskanen Ping Guo Laboratory of Image Processing and Pattern Recognition Beijing Normal University Beijing China Department of Automation and Systems Technology Aalto University School of Electrical Engineering Finland Tampereen yliopisto - Hervannan kampus Tampere Pirkanmaa FI

In this paper, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for the classification of the epileptic electroencephalogram (EEG) signals. The ANFIS combines the adaptation capability of the neural networks and the fuzzy logic-based qualitative approach together. A given input/output data set is deployed to construct a fuzzy inference system, whose membership function parameters are trained using a back propagation algorithm in combination with a least squares method. However, the training method sometimes may lead to local optima. We here propose a new strategy of hybrid training algorithm based on the fusion of the ANFIS and Harmony Search (HS), HS-ANFIS, which is adopted to tune all the parameters of the ANFIS. The validity of our method is verified by numerical experiments.

关键词： Electroencephalography Epilepsy Feature extraction Training pattern classification Adaptive systems Expert systems

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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...

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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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Face recognition Research Based on Anti-Symmetrical Wavelet and Eigenface

Face Recognition Research Based on Anti-Symmetrical Wavelet ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qian Yin Zhi-Yong Yuan Ying Kong Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science Wuhan University of China Wuhan China School of Computer Science & Technology Beijing Institute of Technology Beijing China

In this paper, a new human face recognition method based on anti-symmetrical biorthogonal wavelet transformation (ASBWT) and eigenface was proposed. First the anti-symmetrical biorthogonal wavelet is chosen to degrade the face image dimension, meanwhile complete the process of face location and segmentation; And then human face is reverted through the face space of eigenface, the traditional average human face is replaced in the within-class scatter matrix. This within-class scatter matrix is used to calculate within-class and between-class distance proportion as a rule function, calculate the twice eigenface through discrete Karhunen-Loeve transform (DKLT), and use singular value decomposition (SVD) method to calculate the eigenvector. Finally we compute the weights and classify the face images. The results show that the proposed method has higher recognition rate and more robust than the traditional eigenface analysis method.

关键词： Face recognition Scattering Matrix decomposition image coding Humans Matrices Degradation Robustness Wavelet analysis Fourier transforms

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Quantification of 3-Dimensional Confluence-Atrial Morphology in Supracardiac Total Anomalous Pulmonary Venous Connection

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JACC: Asia 2024年第8期4卷 594-606页

作者： Shi, Guocheng Huang, Meiping Pei, Yuchen Huang, Peng Wen, Chen Shentu, Jin Zhang, Hao Zhu, Zhongqun Zhong, Yumin Wang, Lisheng Chen, Huiwen Department of Cardiothoracic Surgery Congenital Heart Center Shanghai Children's Medical Center Shanghai Jiao Tong University School of Medicine Department of Catheterization Laboratory Guangdong Cardiovascular Institute Guangdong General Hospital Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Department of Cardio-Thoracic Surgery Hunan Children's Hospital Changsha Department of Radiology Shanghai Children's Medical Center Shanghai Jiao Tong University School of Medicine

Background: Pulmonary vein stenosis (PVS) continues to be a major complication after surgical repair of total anomalous pulmonary venous connection (TAPVC). Recent studies suggest that the morphology of pulmonary venous confluence and the left atrium (LA) is associated with PVS. However, there are limited data on the prognostic value of integrating quantitative confluence-atrial morphology into risk stratification. Objectives: This study sought to evaluate the prognostic impact of novel imaging metrics derived from 3-dimensional (3D) computed tomography angiography (CTA) modeling on postsurgical PVS (PPVS) in the supracardiac TAPVC (sTAPVC) setting. Methods: Patients undergoing sTAPVC repair in 2017 to 2022 from 3 centers were retrospectively reviewed. Study investigators developed 3D CTA modeled geometric features to quantify confluence-atrial morphology that were analyzed with regard to PPVS. Results: Of the 162 patients (median age 61 days;55% having preoperative pulmonary venous obstruction [prePVO]) included, 47 (29%) with PPVS at a median of 1.5 months ([quartile 1-quartile 3: 1.5-3.0 months]). In the univariable analysis, the indexed total volume of the LA and confluence (iTVLC) and the ratio of the corresponding confluence length to the mean distance between the LA and confluence (CCL/mDBLC ratio) were significantly associated with PPVS. In a multivariable model adjusting for prePVO and age, the iTVLC and CCL/mDBLC ratio independently predicted PPVS (HR: 1.15;95% CI: 1.06-1.25;and HR: 1.20;95% CI: 1.08-1.35, respectively, all P < 0.01). Specifically, an iTVLC ≥20 cm³/m² and a CCL/mDBLC ratio ≥7.7 were significantly associated with a reduced risk of PPVS. Conclusions: Quantification of 3D confluence-atrial morphology appears to offer a deeper and better metric to predict PPVS in patients with sTAPVC. © 2024 The Authors

关键词： 3-dimensional computed tomography congenital heart disease pulmonary vein stenosis total anomalous pulmonary venous connection

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Impulse noise removal using linear prediction model

Impulse noise removal using linear prediction model

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4th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, ITELSIKS 1999

作者： Prudyus, Ivan Voloshynovskiy, Sviatoslav Rytsar, Yuriy Holotyak, Taras Radio Engineering Faculty State University Lvivska Polytechnika 12 S.Bandery Str. Lviv 290646 Ukraine Coordinated Science Laboratory University of Illinois College of Engineering 1308 West Main Street Urbana IL 61801-2307 United States Department of Image Processing and Pattern Recognition Institute of Physics and Mechanics National Academy of Science of Ukraine 5 Naukova str. Lviv Ukraine

ISBN: (纸本)078035768X

Noise removal is an important problem in many applications. In this paper a new two-step scheme of the decision-based impulse noise removal method by means of contaminated pixel detection is proposed and comparison with direct order statistic filtering is given. The proposed methods satisfy both objective and subjective image quality. © 1999 IEEE.

关键词： Impulse noise

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Vehicle Routing Problem with Time Windows using Hybrid Metaheuristic Dragonfly Algorithm and Variable Neighborhood Search: Work on Progress 11

Vehicle Routing Problem with Time Windows using Hybrid Metah...

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11th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2024

作者： Yunita, Yunita Stiawan, Deris Rini, Dian Palupi Sriwijaya University Faculty of Computer Science Indonesia Sriwijaya University Intelligent System Research Group Faculty of Computer Science South Sumatera Palembang Indonesia Sriwijaya University Communication Network and Information Security Research Group Faculty of Computer Science South Sumatera Palembang Indonesia Sriwijaya University Image Processing Dan Pattern Recognition Laboratory Group Faculty of Computer Science South Sumatera Palembang Indonesia

ISBN: (纸本)9798350355314

One of the problems with Smart Transportation is the problem of cost and travel time. This problem is known as the Variable Routing Problem (VRP). In some real cases, in addition to considering route selection, there are limitations on the capacity and time period for the vehicle to serve each customer known as Time Windows, so VRP has developed into Variable Routing Problem with Time Windows (VRPTW). One way to solve VRPTW is to use metaheuristic methods. However, the metaheuristic method has a weakness, which are it can get stuck in local optimums and fail to find better global solutions. To overcome this, a combination with other methods or known as hybrid is needed. The formulation of this research problem is how to develop a Smart transportation model using a metaheuristic hybrid algorithm. The purpose of this study is to develop a Smart transportation model using a metaheuristic hybrid algorithm. The method used is to combine two metaheuristic algorithms, which are the Dragonfly Algorithm (DA) and the Variable Neighborhood Search (VNS). The result of this research is a new algorithm model which is a hybrid between DA and VNS. Through a combination of global exploration using DA and local exploitation using VNS, this algorithm is expected to be able to find a better solution and faster convergence in solving VRPTW problems © 2024 IEEE.

关键词： Travel time

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Object based video watermarking scheme using inertia ellipse and shape adaptive DCT

Object based video watermarking scheme using inertia ellipse...

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IEEE Workshop on Multimedia Signal processing

作者： Guo Jie Shi Peng-fei Fang Tao Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China The State Key Laboratory of Information Security Chinese Academy and Sciences Beijing China Chinese Academy of Seiencer The State Key Laboratory of Information Security Beijing China

ISBN: (纸本)0780377133

Video object (VO) is an important concept in MPEG-4. For objects can be easily manipulated without visible distortion, the copyright protection of video objects becomes an important issue. This paper presents a watermarking scheme for video objects. Different from other methods, the proposed scheme employed inertia ellipse to achieve fast synchronization recovery in case the object was manipulated. Shape adaptive DCT and visual mask were combined to embed the watermark into the arbitrarily shaped object, which was designed to achieve the trade-off between the invisibility and the robustness. Experiments show that our algorithm is robust to object manipulations such as rotations, translations, scaling and lossy compression. Our scheme can be easily incorporated into the object-based coding framework of MPEG-4.

关键词： Watermarking Shape Discrete cosine transforms MPEG 4 Standard Robustness image coding Streaming media Discrete wavelet transforms image processing image recognition

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