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Multi-focus image Fusion Scheme Using Adaptive Dual-Channel Pulse Coupled Neural Network

Multi-focus Image Fusion Scheme Using Adaptive Dual-Channel ...

引用

International conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Yongxing Jia Chuanzhen Rong Ying Zhu Yu Yang Yuan Wang College of Communications Engineering PLA University of Science and Technology Nanjing China

ISBN: (纸本)9781509007691

image fusion combines information from multiple images of the same scene to obtain a composite image which is more suitable for further image processing tasks. By analyzing the pulse coupled neural network(PCNN), and combining with the characteristics of multi-focus image, a novel PCNN model dual-channel PCNN(Dual-channel PCNN) was proposed in this paper. The mathematical model was first given, then a novel sum-modified-Laplacian(NSML) was selected as the focus measure to compute the sharpness of the source images, and then the sharpness of each pixel was used as the linking strength of the corresponding neuron. Experimental results show that the proposed method outperforms some previous fusion methods, both in visual effect and objective evaluation criteria.

关键词： Neurons image fusion Joining processes Mathematical model Firing Biological neural networks

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Dynamic Volumetric Video Coding with Tensor Decomposition

Dynamic Volumetric Video Coding with Tensor Decomposition

引用

IEEE visual communications and image processing (VCIP)

作者： Ju-Yeon Shin Yeoneui Kim Je-Won Kang Gun Bang Dept. of Electronic and Electrical Engineering and Graduate Program in Smart Factory Ewha Womans University Seoul South Korea Electronics and Telecommunications Research Institute Daejeon South Korea

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

Recently, volumetric video coding based on neural radiance fields has gained significant attention for storing and transmitting three-dimensional (3D) scenes captured from multi-view video. Because the neural networks are trained to produce novel view synthesis of surrounding 3D scenes, compressing the model and then rendering the colors and geometry through the decompressed model can be utilized as a 3D video coding system. However, although this approach provides superior performance compared to conventional 3D video coding standards using depth video, challenges remain in reducing overall model sizes to improve coding efficiency. In this paper, we propose a novel dynamic volumetric video coding technique that employs a Group of Volume (GoV) to divide multi-view video sequences into smaller chunks, addressing complex temporal dynamics. Our method uses volumetric video features represented with 3D spatial and temporal tensor matrices and vectors and encodes them with the GoVs. The tensors are compressed by existing 2D video codec, allowing for fast rendering and easing deployment. Experimental results validate that our method not only reduces memory footprint but also maintains high-quality rendering as compared to state-of-the-art studies.

关键词： Video coding Solid modeling Three-dimensional displays image coding Tensors visual communication Video sequences Rendering (computer graphics) Video codecs Standards

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Orthogonal Coded Multi-view Structured Light for Inter-view Interference Elimination

Orthogonal Coded Multi-view Structured Light for Inter-view ...

引用

IEEE visual communications and image processing (VCIP)

作者： Zaichao Sun Guochao Qian Zhaoyu Peng Weiju Dai Dongjun Sun Gongyuan Zhang Nongtao Zhang Jun Xu Ren Wang Chunlin Li Electronic Power Research Institute of Yunnan Electronic Power Grid Co. Ltd Kunming China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

Rapid 3D reconstruction of dynamic scenes is very useful in 3D object structure analysis, accident avoidance for UAV, and other visual applications. Against dynamic scenes, coded structured light methods have been proposed to obtain the depth information of an object in 3D world, and most of them are based on spatial codification. A brutal truth is that two or more cameras and projectors from different viewpoints are needed to measure the dynamic scene simultaneously for rapid 3D reconstruction. However, when two traditional patterns, especially the binaries, are mutually overlapped, interference between them arises to a new challenge to 3D reconstruction. Traditional patterns can hardly be separated from each other, which surely influence the quality of the 3D reconstruction. To eliminate the interference problem, we propose a scheme of orthogonal coded multi-view structured light systems, which can obtain accurate of depth maps for a scene. Besides, we also test the stability of the orthogonal patterns by establishing three different scenes and making a comparisons to traditional patterns. New state-of-the-art results can be obtained by our scheme in the experiments.

关键词： Interference Cameras Three-dimensional displays Power system dynamics Sun image coding Decoding

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A robust bread defect detection and counting system

A robust bread defect detection and counting system

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International conference on Advanced Communication Technology (ICACT)

作者： Ilkoo Ahn Michael Moonshin Zo Changick Kim Visual Information Processing Laboratory Information and Communications University Daejeon South Korea CasaTech Suwon South Korea

In this paper, an automated visual inspection method is presented to detect defect and count breads for the use in bread production. Cost reduction in production and inspection processes is of big concern to bread manufacturers. Inspecting bread by human eyes must be a tedious job for human inspectors, which might result in high inspection error. Hence, automated inspection systems are greatly required. In this work, the bread image is binarized firstly. If several breads are adjacent to each other, those are separated using K-cosine corner detection algorithm. Next, defect detection is conducted by taking object's area and Hu's invariant moments. Experimental results indicate that the proposed method can be efficiently used in the bread inspection system.

关键词： Robustness Inspection Shape Humans Costs Production Food industry Packaging Discrete wavelet transforms Information processing

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Deep LSTM Transfer Learning for Personalized ECG Anomaly Detection on Wearable Devices 5th

Deep LSTM Transfer Learning for Personalized ECG Anomaly Det...

引用

5th International conference on Cognitive Systems and Signal processing, ICCSIP 2020

作者： Deng, Xin Zhou, Jianqiao Xiao, Bin Xiang, Xiaohong Yuan, Yi Key Laboratory of Data Engineering and Visual Computing Chongqing University of Posts and Telecommunication Chongqing400065 China Chongqing Key Laboratory of Image Recognition Chongqing University of Posts and Telecommunication Chongqing400065 China

ISBN: (纸本)9789811623356

Cardiovascular diseases are the main cause of global non-communicable deaths, accounting for about one-third of the total deaths in the world. Wearable devices are used for early monitoring and early prevention of cardiovascular diseases. Aimed at the low configuration, low power consumption and personalized characteristics of the wearable ECG equipment, a transfer learned with deep LSTM model is proposed in this work. The model is computational efficient and serves as the patient-specific ECG anomaly detector that can be used on the wearable devices. Based on the MIT-BIH open dataset, the experiment results show that the transfer learning model produces superior weighted F2 scores compared to the general model and the naive model for detecting ECG anomalies, such as the premature ventricular contractions and atrial premature beats. The transfer learning model proposed here provides a sensitive, personalized ECG anomaly detection mechanism that has the added benefit of light, quick and robust learning process to be used on wearable devices, which can meet the requirement of ECG monitoring for patients by wearable devices. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Electrocardiograms

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Compressing 3D Gaussian Splatting via a Generalizable Neural Coder

Compressing 3D Gaussian Splatting via a Generalizable Neural...

引用

IEEE visual communications and image processing (VCIP)

作者： Junteng Zhang Tong Chen Hao Zhu Dong Wang Dandan Ding Zhan Ma Nanjing University Nanjing China Interdisciplinary Research Center for Future Intelligent Chips (Chip-X) Nanjing University Suzhou China OPPO Inc. Nanjing China Hangzhou Normal University Hangzhou China

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

As a promising technique for 3D representation, 3D Gaussian Splatting (3DGS) offers fast rendering speed and high fidelity while generating large data volumes. This challenges storage and transmission, so an efficient compression solution is required. Existing implicit methods require pre-scene optimization (online), leading to a long optimization time. By contrast, this paper regards the 3DGS as a point cloud and pre-trains a generalizable (offline) neural coder for compression. After obtaining the 3DGS representation, we focus on the data compression process, which is friendly to applications already equipped with a PCC codec. The neural coder employed is extended from a typical AIbased point cloud compression method, which uses a multiscale and multistage framework to exploit spatial correlations across scales and stages for conditional coding. Experimental results show that our method significantly outperforms existing 3DGS representations without compromising fidelity, achieving more than 39× and 6.8× compression ratio compared to the original 3DGS and SOTA Scaffold-GS, respectively. More importantly, our approach does not require additional time to optimize the compression model.

关键词： Point cloud compression image coding Three-dimensional displays Correlation Codecs visual communication Rendering (computer graphics) Optimization

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Codec designs for image browsing

Codec designs for image browsing

引用

IEEE International conference on Multimedia Computing and Systems (ICMCS)

作者： Iyengar Panchanathan Multimedia Communications Research Laboratory Department of Electrical Engineering University of Ottawa Ottawa ONT Canada

We propose codec designs for image browsing. image/video browsing is an important requirement in many multimedia applications. In image browsing, a lower resolution version of the image is first viewed. Upon request, the resolution is further enhanced until an acceptable fidelity is obtained. Recently, many new codecs have been designed for image/video compression. However these codecs are not directly applicable for image browsing as they cannot interact with the user. In this paper, we propose a codec design based on Gabor decomposition which is well adapted for image browsing applications. However we note that the generic design can be implemented with any compression algorithm. Gabor decomposition is a promising approach for image browsing. The Gabor basis functions match the human visual profiles and hence result in better subjective quality compared to JPEG. For example, Gabor decomposition does not suffer from the blocking artifacts prevalent in JPEG-DCT. The proposed codec can achieve real-time performance, is simple and modular and hence can be implemented in VLSI.< >

关键词： Multimedia systems Data compression image coding Codecs image processing

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3D Imaging of Sparse Wireless Signal Reconstructions via Machine Learning

3D Imaging of Sparse Wireless Signal Reconstructions via Mac...

引用

IEEE International conference on communications (ICC)

作者： Scott Fowler Gabriel G. Baravdish George Baravdish Communications and Transport Systems Linköping University Norrköping Sweden Media and Information Technology Linköping University Norrköping Sweden Physics Electronics and Mathematics Linköping University Norrköping Sweden

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

Wireless devices have been used to investigate the environment and to understand our physical world. In this work, we undertake the challenging problem of identifying location of obstacles and objects by WiFi signals. Gathering wireless sensory data to form an image is difficult since wireless signals are susceptible to multipath. Moreover, reconstructing an image of unknown objects based on the measurements of sparse signals is an ill-posed problem. To tackle these problems, we first present a linear model using received signal strength indicator (RSSI) measurements. We define the sparse beamforming problem as an ℓ 0 -norm optimization problem, then use the iterative reweighted ℓ 1 heuristic algorithm to obtain an optimal solution as a multipath. Finally, the multipath fading is removed by using Machine Learning. More specifically, we use Support Vector Regression (SVR) to identify a clear image of the unknown object. Our results show that the proposed method can reconstruct signals as a 3D image with a satisfactory visual appearance, i.e. the generated data mesh is well defined and smooth compared to previous work.

关键词： Wireless communication Wireless sensor networks image reconstruction Signal processing algorithms Three-dimensional displays Object recognition Kernel

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A system for the automatic extraction of 3-D facial feature points for face model calibration

A system for the automatic extraction of 3-D facial feature ...

引用

IEEE International conference on image processing

作者： Yong Yan K. Challapali Video Communications Department Philips Research Briarcliff Manor NY USA

The emergence of the MPEG-4 standard has facilitated the development of new approaches to very-low bitrate coding, including model-based coding for human faces. As a tool in the synthetic/natural hybrid coding part of the standard, a face object is defined in terms of its shape-consisting of a set of facial feature points and texture. In addition, this face object can be animated by controlling these facial feature points to obtain a visual manifestation of speech and facial expression. However, the extraction of these facial feature points based on a particular human face is not a trivial task, and lies outside the scope of the MPEG-4 standard. In this paper, we introduce a system that automatically extracts 3-D facial feature points and calibrates a generic face model to a particular speaker's face. Our approach differs from previous work in that we extract facial feature points in 3-D using a stereoscopic camera leading to an automatic robust calibration of the face model to the particular face. Preliminary experimental results show promising performance.

关键词： Facial features Calibration Facial animation MPEG 4 Standard Humans Face Standards development Bit rate Speech Cameras

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Center-free intuitionistic fuzzy c-means clustering algorithm based on similarity of hybrid spatial membership for image segmentation

Center-free intuitionistic fuzzy c-means clustering algorith...

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Natural Language processing (ICNLP), International conference on

作者： Lan Rong Wang Shumin He Hu Zhao Feng Yu Haiyan Zhang Lu School of Communications and Information Engineering Xi’an University of Posts and Telecommunications Xi’an China

In order to address the issue that the center-free fuzzy c-means (CFFCM) clustering algorithm does not consider the texture features and spatial information of pixels, and the time complexity is too high, a center-free intuitionistic fuzzy c-means clustering algorithm based on similarity of hybrid spatial membership for image segmentation is proposed. In the proposed algorithm, the voting model is used to generate intuitionistic fuzzy sets (IFS), and the generated hesitation degree and membership degree are combined with spatial information to design a spatial intuitionistic membership degree similarity model. This model can deal with the similarity between pixels and classes in gray information, so the segmentation efficiency is improved. At the same time, the intuitionistic fuzzy local binary pattern (IFLBP) operator is used to extract the image texture information and introduce it into the objective function. Spatial membership similarity model is used to process texture information and improve the segmentation accuracy of the algorithm. The results of simulation experiment show that the proposed has advantages in both visual effect and evaluation index.

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