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检索条件"任意字段=18th Image Processing: Algorithms and Systems Conference, IPAS 2020"

共 258 条记录，以下是161-170 订阅

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High-dimensional discriminant analysis and its application to color face images

High-dimensional discriminant analysis and its application t...

引用

International conference on Pattern Recognition

作者： Zhizheng Liang Biocomputing center Computing of Department Shenzhen Graduate School of Harbin Institute of Technoloy China

ISBN: (纸本)0769525210

Multilinear algebra plays an important role in signal processing. In this paper, a multilinear generalization of linear discriminant analysis is discussed. Similar to HOSVD, an iterative algorithm is developed for solving high-dimensional linear discriminant analysis. Meanwhile, a non-iterative algorithm is also proposed. In addition, HDLDA provides a unified framework for classical LDA and 2DLDA. Experimental results on color face images show the effectiveness and usefulness of the proposed method

关键词： image color analysis image analysis Tensile stress Linear discriminant analysis Algebra Signal processing algorithms Iterative algorithms Computer vision Multidimensional systems Matrix decomposition

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Machine Vision Based Weight Prediction for Flatfish

Machine Vision Based Weight Prediction for Flatfish

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International conference on Control, Automation and systems

作者： K. H. Hwang J. W. Choi School of Mechanical Engineering Pusan National University Busan Korea

ISBN: (纸本)9781538670804;9788993215168

In fisheries industry, flatfish accounts for about half of the domestic fish production and is a specie with active aquaculture activities. As flatfish grows, classification according to the size should be periodically carried out for efficient growth. In this paper, the correlation between area and weight of flatfish required for classification algorithms using machine vision is derived. 120 simulations are performed using flatfish models and the area is obtained through image processing. In image processing process, the area of flatfish model is calculated using a reference square known in size. the weight of actual fish corresponding to the length of the model is obtained using the reference equation. then, regression analysis is performed to derive the interpolation of linear and power equations which show correlation between area and weight of the flatfish.

关键词： Machine vision Regression analysis Parameter estimation image processing

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Alzheimer’s Disease Diagnosis Based on Collaborative Learning Augmented algorithms 18th

Alzheimer’s Disease Diagnosis Based on Collaborative Learn...

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18th Chinese Intelligent systems conference, CISC 2022

作者： Gao, Libin Hu, Zhongyi Li, Zuoyong Lu, Xingjin Li, Rui Tong, Yinsheng Lin, Dehou College of Computer Science and Aritificial Intelligence Wenzhou University Wenzhou325035 China Key Laboratory of Intelligent Image Processing and Analysis Wenzhou325035 China College of Computer and Control Engineering Minjiang University Fuzhou350108 China

ISBN: (纸本)9789811962028

In this study, a novel training method is innovatively proposed to address the problem of poor generalisation of trained models due to imbalance in Alzheimer’s disease (AD) data. the method alternates AD image data with dog and cat data from natural images for collaborative learning training across datasets, enhancing the generalisation ability of the models. At the same time, inspired by current work related to attention mechanisms under the field of computer vision, the model is reconstructed and an attention module is added to the model to further improve the accuracy of the model. the experimental results show that the method has good classification performance and provides new ideas for the diagnosis of other brain diseases. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolutional neural networks

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Adaptation of parameterized interpolation algorithms of multidimensional signals for hierarchical and interpolation compression methods 6

Adaptation of parameterized interpolation algorithms of mult...

引用

6th International conference Information Technology and Nanotechnology. Session image processing and Earth Remote Sensing, ITNT-IPERS 2020

作者： Gashnikov, Mikhail Department of GIS ITsec Samara National Research University MMIP Laboratory Image Processing Systems Institute of RAS Branch of the FSRC "Crystallography and Photonics" RAS Samara Russia

We adapt parameterized multidimensional signal interpolators for hierarchical compression methods and interpolation compression methods based on the coding of quantized post-interpolation residues. the considered interpolators automatically select the most appropriate interpolating function at each point of the signal using a parameterized decision rule. We propose a set of interpolation functions for these compression methods. We select the optimization criterion for the proposed interpolator. the optimization criterion is based on minimization the entropy of the quantized post-interpolation residues. We solve the optimization problem of the adaptive parameterized interpolator according to this criterion. We perform computational experiments to study the proposed interpolators in natural multidimensional signals. the experimental results confirm that the use of the adaptive interpolators can significantly increase the effectiveness of the mentioned methods of multidimensional signals compression. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： Interpolation

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Parallel image processing on the Sunway Many-Core Processor

Parallel Image Processing on the Sunway Many-Core Processor

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IEEE International conference on High Performance Computing and Communications (HPCC)

作者： Meiting Zhao Rui Liu Yi Liu Kaida Song Depei Qian State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China Sino-German Joint Software Institute Beihang University Beijing China

ISBN: (纸本)9781509042982

Many image processing algorithms have been parallelized successfully on many-core processors, such as GPU and Intel Xeon Phi. In this paper, we choose the Sunway many-core processor SW26010, which is a new processor designed and made in China that constitutes the current NO.1 supercomputer Sunway TaihuLight. this paper firstly introduces the architecture of Sunway SW26010 processor and two representative image processing algorithms: local binary pattern (LBP) and histogram of oriented gradient (HOG). Furthermore we propose a method of parallel implementation, and the experimental results of this method show that the speedup can be up to 170 for LBP and 33 for HOG. then two optimized methods are brought forward based on this parallel implementation, including the optimization of program and parallel design. We optimize the program by using the method that combined step transmission and software prefetching. From the experiment results of the first optimization we can know that the maximum speedup can reach 310 for LBP with processing high-resolution images and 83 for HOG. then we optimize the parallel design by using a coarse grained parallel method, and the experimental results show that the speedup can be up to 370 for LBP and 95 for HOG when processing low-resolution images. Finally, we investigate the scalability of our parallelism on the Sunway TaihuLight with different number of processor nodes, and the experiment results prove that the two algorithms' parallel design and implementation have better expansibility.

关键词： Algorithm design and analysis image processing Supercomputers Computer architecture Clustering algorithms Optimization Parallel algorithms

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Low-complexity image coder/decoder with an approaching-entropy quad-tree search code for embedded computing platforms

Low-complexity image coder/decoder with an approaching-entro...

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IEEE International conference on image processing

作者： Tao Ma Pradhumna Shrestha Michael Hempel Dongming Peng Hamid Sharif Department of Computer and Electronics Engineering University of Nebraska Lincoln USA

In this paper, we propose a fast, simple and efficient image codec applicable for embedded processing systems. Among the existing image coding methods, wavelet quad-tree is a foundation leading to an efficient structure to encode images. By searching significant coefficients along quadtrees, an embedded efficient code can be obtained. In this work, we exploit hierarchical relations of the quad-tree structure in terms of searching entropy and present a quadtree searching model that is very close to the searching entropy. By applying this model, our codec surpasses SPIHT [1] by 0.2-0.4 db over wide code rates, and its performance is comparable to SPIHT with arithmetic coding and JPEG2000 [2]. With no additional overhead of arithmetic coding, our code is much faster and simpler than SPIHT with adaptive arithmetic coding and the more complicated JPEG2000 algorithms. this is a critical factor sought in embedded processing in communication systems where energy consumption and speed are priority concerns. Our simulation results demonstrate that the proposed codec is about twice as fast with very low computational overheads and comparable coding performances than existing algorithms.

关键词： image coding Entropy Codecs Transform coding Algorithm design and analysis Computational modeling Communication systems

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QUALITY CONTROLLED ARTIFACT REDUCTION

QUALITY CONTROLLED ARTIFACT REDUCTION

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European Signal processing conference

作者： Martin Richter Mathias Stober Hartmut Schroder Circuits and Systems Lab TU Dortmund University

Strongly varying input content to modern flat panel displays makes highly adaptive algorithms mandatory. On the one hand, low quality content is dominated by coding artifacts and therefore strong artifact reduction can increase image quality. On the other hand, too strong processing removes image details in high quality video. these contrary optimization criteria cannot be fulfilled easily by simple processing strategies. this paper proposes a framework utilizing different artifact reduction algorithms while their output is controlled by objective quality measures selecting the most suitable algorithm at run-time. thus, a dynamic selection of the optimal processing for each input scenario over a wide quality level is possible. Integrating a feedback loop and applying the process again can further enhance the output quality.

关键词： artifact reduction output quality Quality standards optimal criterion reduction Feedback loop image quality Flat panel displays Hand

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Least-squares Optimal Relative Planar Motion for Vehicle-mounted Cameras

Least-squares Optimal Relative Planar Motion for Vehicle-mou...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Hajder, Levente Barath, Daniel Eotvos Lorand Univ Dept Algorithms & Their Applicat Budapest Hungary Czech Tech Univ Visual Recognit Grp Dept Cybernet Prague Czech Republic MTA SZTAKI Machine Percept Res Lab Budapest Hungary

ISBN: (纸本)9781728173955

A new closed-form solver is proposed minimizing the algebraic error optimally, in the least squares sense, to estimate the relative planar motion of two calibrated cameras. the main objective is to solve the over-determined case, i.e., when a larger-than-minimal sample of point correspondences is given - thus, estimating the motion from at least three correspondences. the algorithm requires the camera movement to be constrained to a plane, e.g. mounted to a vehicle, and the image plane to be orthogonal to the ground.(1) the solver obtains the motion parameters as the roots of a 6th degree polynomial. It is validated both in synthetic experiments and on publicly available real-world datasets that using the proposed solver leads to results superior to the state-of-the-art in terms of geometric accuracy with no noticeable deterioration in the processing time.

关键词： Cameras Transmission line matrix methods Robot vision systems Estimation Automobiles Geometry

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Bayesian image Analysis in Fourier Space Using Data-Driven Priors (DD-BIFS) 18th

Bayesian Image Analysis in Fourier Space Using Data-Driven P...

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18th International conference on Information processing and Management of Uncertainty in Knowledge-Based systems, IPMU 2020

作者： Kornak, John Boylan, Ross Young, Karl Wolf, Amy Cobigo, Yann Rosen, Howard University of California San FranciscoCA94143 United States

ISBN: (纸本)9783030501525

Statistical image analysis is an extensive field that includes problems such as noise-reduction, de-blurring, feature enhancement, and object detection/identification, to name a few. Bayesian image analysis can improve image quality, by balancing a priori expectations of image characteristics, with a model for the noise process via Bayes theorem. We have previously given a reformulation of the conventional Bayesian image analysis paradigm in Fourier space, i.e. the prior distribution (the prior) and likelihood are given in terms of spatial frequency signals. By specifying the Bayesian model in Fourier space, spatially correlated priors, that are relatively difficult to model and compute in conventional image space, can be efficiently modeled as a set of independent processes across Fourier space. the originally inter-correlated and high-dimensional problem in image space is thereby broken down into a series of (trivially parallelizable) independent one-dimensional problems. In this paper we adapt this Fourier space process into a data-driven framework in which the Fourier space priors are built empirically from a database of images and then used to enhance future images. We will describe the data-driven Bayesian image analysis in Fourier space (DD-BIFS) modeling approach, illustrate it’s computational efficiency and speed. Finally, we give specific applications of DD-BIFS to improve the quality of arterial-spin-labeling (ASL) perfusion images via a database of human brain positron emission tomography (PET) images. © 2020, Springer Nature Switzerland AG.

关键词： Quality control

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Experiments on improving lossless compression of biometric iris sample data

Experiments on improving lossless compression of biometric i...

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International conference on systems, Signals and image processing, IWSSIP

作者： Herbert Stögner Georg Weinhandel Andreas Uhl School of Communication Engineering for IT Carinthia University of Applied Sciences Klagenfurt Austria Department of Computer Sciences University of Salzburg Salzburg Austria

the impact of using different lossless compression algorithms when compressing biometric iris sample data from several public iris databases is investigated. In particular, we relate the application of dedicated lossless image codecs like JPEG-LS, CALIC, and PNG, lossless variants of lossy codecs like JPEG2000 and JPEG XR, and two general purpose compression schemes to rectilinear iris sample imagery from seven public databases. the application of additional prediction as a preprocessing strategy as well as a conversion to a set of binary images to enable JBIG application is evaluated. the results are discussed in the light of the recent ISO/IEC FDIS 19794-6 and ANSI/NIST-ITL 1-2011 standards and IREX recommendations.

关键词： image coding Transform coding Iris recognition Databases Gray-scale ISO standards IEC standards

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