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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Hui Chen Jingqi Yan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781479905607

In this paper, we describe a novel 3D shape retrieval method based on new features. The features are extracted for 3D points based on a 2D attribute space which consists of two bidirectional 3D shape attributes, one of which along the shape surface direction and the other along the shape content direction perpendicular to the former. We define this features as Point Bidirectional Features (PBFs), which can reflect not only the global shape but also the local content. For simplicity, we choose the geodesic distance (GD) and the shape diameter function (SDF) to construct PBFs. Given a database of 3D shapes and a query shape, the proposed retrieval method adopts a shape similarity measurement based on 3D points matching with PBFs to decide which is the most similar shape from the database. To reduce cost of computation and feature storage, a shape simplification algorithm is integrated into this method. Additionally, a simple but effective point correspondence mechanism with K-Nearest Neighbor (KNN) assignment is designed for this retrieval method. Experimental results demonstrate the effectiveness of the proposed features and method.

关键词： Shape Three-dimensional displays Histograms Solid modeling Computational modeling Feature extraction Databases

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Dual-channel noise reduction via sprase representations

Dual-channel noise reduction via sprase representations

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IEEE Workshop on Multimedia Signal processing

作者： Jiancheng Zou Jingsai Liang Xin Yang Institute of Image Processing and Pattern Recognition North-China University of Technology Beijing China

An effective dual-channel noise reduction algorithm is proposed based on sparse representations. The algorithm is composed of the following steps. Firstly, overlapping patches sampled from two channels together instead of each channel one by one are trained to be a dictionary via K-SVD. Secondly, OMP(Orthogonal-Matching-Pursuit) reconstruction algorithm is applied to obtain the sparse coefficients of patches using the dictionary. Thirdly, the denoising speech can be obtained by the updated coefficients. Lastly, the above three steps are iterated to get clearer speech until some conditions are reached. Experimental results show that this algorithm performs better than that with single channel.

关键词： Dictionaries Speech Noise reduction Matching pursuit algorithms Sparse matrices Gaussian noise Discrete cosine transforms

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Nonlinear multi-scale contrast enhancement for chest radiograph

Nonlinear multi-scale contrast enhancement for chest radiogr...

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IEEE International Conference on image processing

作者： Xuanqin Mou Min Zhang Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an Shaanxi China

Recently, extensive research and application on contrast enhancement of radiographs based on multi-scale decomposition of the images have validated its higher performance than regular techniques. However, to some extent, conventional multi-scale methods suffered from the introduction of visible artifacts. In this work, we present an algorithm for nonlinear chest radiograph contrast enhancement algorithm within the multi-scale decomposition architecture in spatial domain. In particular, one kind of nonlinear enhancement function is designed by exploiting local contrast information. The main contribution of this model is the local adaptive enhancement ability, which can avoid visible artifacts, while keeping the same detail enhancement ability. In the meantime, no excessive noise is amplified, comparing to conventional methods. Finally, an evaluation using a chest image is provided to demonstrate the effectiveness of the proposed algorithm.

关键词： Computer architecture Diagnostic radiography Humans Rendering (computer graphics) Band pass filters X-ray imaging Kernel image processing pattern recognition Cardiology

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An Unsupervised Person Search Method for Video Surveillance 22

An Unsupervised Person Search Method for Video Surveillance

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8th International Conference on Computing and Artificial Intelligence, ICCAI 2022

作者： Feng, Deying Yang, Jie Wei, Yanxia Xiao, Hairong Zhang, Laigang School of Mechanical and Automotive Engineering Liaocheng University China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Liaocheng University China

ISBN: (纸本)9781450396110

We propose an unsupervised person search method for video surveillance. This method considers both the spatial features of persons within each frame and the temporal relationship of the same person among different frames. Thus, the spatial features are extracted by region convolutional neural network, and the temporal relationship is organized by gate recurrent unit. The spatio-temporal features are generated by the following average pooling layer and indexed by locality sensitive hashing. A surveillance video database is constructed to evaluate the proposed method, and the experimental results demonstrate that our method improves the search accuracy by utilizing the spatio-temporal features. © 2022 ACM.

关键词： Monitoring

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A robust method for high-accuracy microbe identification based on image processing

A robust method for high-accuracy microbe identification bas...

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IEEE International Conference on Progress in Informatics and Computing (PIC)

作者： Mingqi Cao Yuncai Liu Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai China

ISBN: (纸本)9781479920327

We present a novel fast method based on computer vision to identify microbe The proposed method is simple but absolutely effective It combines approximate parallel light source and industrial camera, to automatically accomplish the bacteria identification and monitor the growing states of bacteria during the progress of a drug sensitive test. Based on this method, the color information and turbidity information, which reflect the primary information of drug sensitive tests, can be obtained fast, while processing efficiency can be as high as hundreds of milliseconds per frame. The performance of our method is significantly accurate and robust.

关键词： Feature extraction image color analysis Drugs Monitoring image edge detection Noise Media

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Feature Selection Based on Adaptive Fuzzy Membership Functions

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自动化学报 2006年第4期32卷 496-503页

作者： XIE Yan-Tao SANG Nong ZHANG Tian-Xu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature selection algorithms with artificial neural networks(ANN)usually require normalization of input data,which will probably change some characteristics of original data that are important for *** overcome the problems mentioned above,this paper combines the fuzzification layer of the neuro-fuzzy system with the multi-layer perceptron(MLP)to form a new artificial neural ***,fuzzification strategy and feature measurement based on membership space are proposed for feature selection. Finally,experiments with both natural and artificial data are carried out to compare with other methods,and the results approve the validity of the algorithm.

关键词： Membership function feature selection architecture pruning artificial neural networks

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Computational complexity reduction in eigenspace approaches 7th

Computational complexity reduction in eigenspace approaches

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7th International Conference on Computer Analysis of images and patterns, CAIP 1997

作者： Leonardis, Aleš Bischof, Horst Vienna University of Technology Institute for Automation Pattern Recognition and Image Processing Group Treitlstraße 3/1832 ViennaA-1040 Austria University of LjubIjana Tržaška 25 LjubljanaSI-1001 Slovenia

ISBN: (纸本)3540634606

Matching of appearance-based object representations using eigenimages is computationally very demanding. Most commonly, to recognize an object in an image, parts of the input image are projected onto the eigenspace and the recovered coefficients indicate the presence or absence of a particular object. In general, the process is sequentially applied to the entire image. In this paper we discuss how to alleviate the problems related to complexity. First, we propose to use a focus-ofattention (FOA) detector which is intended to select candidate areas of interest with minimal computational effort. Only at these areas we then recover the coefficients of eigenimages. Secondly, we propose to employ a multiresolution approach. However, this requires that we depart from the standard way of calculating the coefficients of the eigenimages which relies on the orthogonality property of eigenimages. Instead we calculate them by solving a system of linear equations. We show the results of our approach on real data. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Computers

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Energy enhanced tissue texture in spectral computed tomography for lesion classification

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Visual Computing for Industry,Biomedicine,and Art 2019年第1期2卷 138-149页

作者： Yongfeng Gao Yongyi Shi Weiguo Cao Shu Zhang Zhengrong Liang Department of Radiology Stony Brook UniversityStony BrookNY 11794USA Institute of Image Processing and Pattern Recognition Xi’an Jiaotong UniversityXi’an 710049ShanxiChina Departments of Radiology Biomedical EngineeringComputer Scienceand Electrical EngineeringStony Brook UniversityStony BrookNY 11794USA

Tissue texture reflects the spatial distribution of contrasts of image voxel gray levels,i.e.,the tissue heterogeneity,and has been recognized as important biomarkers in various clinical *** computed tomography(CT)is believed to be able to enrich tissue texture by providing different voxel contrast images using different X-ray ***,this paper aims to address two related issues for clinical usage of spectral CT,especially the photon counting CT(PCCT):(1)texture enhancement by spectral CT image reconstruction,and(2)spectral energy enriched tissue texture for improved lesion *** issue(1),we recently proposed a tissue-specific texture prior in addition to low rank prior for the individual energy-channel low-count image reconstruction problems in PCCT under the Bayesian *** results showed the proposed method outperforms existing methods of total variation(TV),low-rank TV and tensor dictionary learning in terms of not only preserving texture features but also suppressing image *** issue(2),this paper will investigate three models to incorporate the enriched texture by PCCT in accordance with three types of inputs:one is the spectral images,another is the cooccurrence matrices(CMs)extracted from the spectral images,and the third one is the Haralick features(HF)extracted from the *** were performed on simulated photon counting data by introducing attenuationenergy response curve to the traditional CT images from energy integration *** results showed the spectral CT enriched texture model can improve the area under the receiver operating characteristic curve(AUC)score by 7.3%,0.42%and 3.0%for the spectral images,CMs and HFs respectively on the five-energy spectral data over the original single energy data *** CM-and HF-inputs can achieve the best AUC of 0.934 and *** texture themed study shows the insight that incorporating clinical important prior information,e.g.,tiss

关键词： Tissue texture Spectral computed tomography Lesion classification Machine learning Bayesian reconstruction

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The Algorithm for Matching 2D Contours Based on V-System

The Algorithm for Matching 2D Contours Based on V-System

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Chinese Conference on pattern recognition (CCPR)

作者： Caixia Zhang Zhihua Miao Fengmei Sun Institute of Image Processing and Pattern Recognition North-China University of Technology Beijing China

Curve matching is one of key issues in computer vision, image analysis and pattern recognition. Based on discrete V-transform, the distance is calculated between curves using the descriptor of V-system to find the matching curves, and then the matching parameters are evaluated in this article. The new approach can find efficiently the rough location of a short extracted image curve in a long reference curve. Different from the existing approaches, it needn't to extract feature points. Extensive tests show that it is efficient.

关键词： pattern matching pattern recognition image processing Computer vision image analysis Feature extraction Testing

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A psychovisual image Quality Metric based on multi-scale Structure Similarity

A psychovisual image Quality Metric based on multi-scale Str...

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IEEE International Conference on image processing

作者： Min Zhang Xuanqin Mou Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an Shaanxi China

In this paper, a universal full-reference (FR) image quality metric based on Edge structure similarity (QMESS) is proposed using spatial position displacement degree of wavelet transform modulus maxima between reference image and distorted image in multi-resolution domain. Firstly, we decompose images in wavelet domain. The structure error between reference images and distorted images is computed based on the statistics of spatial position error of local modulus maxima in wavelet domain. At the same time, peak signal to noise ratio (PSNR) is adopted to evaluate the stochastic noise in images. Finally, the low frequency resolution layer distortion is evaluated by means of the mutual information and the luminance distortion. The three components are combined for the whole visual distortion measurement. From the experiment results, the proposed metric is much better than conventional PSNR method and the state-of-the-art SSIM approach in terms of the performance relative to subjective judgment. Comparing to the excellent VIF method, the proposed method performs better in individual distortions and obtains similar results on cross-distortion type.

关键词： Psychology image quality PSNR Wavelet domain Wavelet transforms Error analysis Stochastic resonance Low-frequency noise Frequency Spatial resolution

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