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Flow Visualization for Complex Fluid Flows via A Structure-enhanced Motion Estimator

IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Chen, Jun Wang, He Hao, Zhifeng Cai, Zemin Mei, Ling Foshan University School of Industrial Design and Ceramic Art Foshan528000 China Foshan University school of Mechatronic Engineering and Automation Foshan528231 China Shantou University College of Science Department of Mathematics Guangdong 515063 China Shantou University Department of Electronic Engineering Guangdong Shantou515063 China Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Techniques Guangdong Shantou515063 China Wuhan University of Science and Technology School of Information Science and Engineering 430081 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation 430074 China Western Michigan University Department of Mechanical and Aerospace Engineering KalamazooMI49008 United States

Flow visualization through motion estimation using time-sequenced images plays a significant role in analyzing and understanding complex flow phenomena, and it is widely used in meteorology, oceanography, medicine, astronomy, experimental fluid mechanics, etc. However, it is difficult for current motion estimators to adapt to illumination changes, remove instable perturbation, and capture diverse motion patterns. In this paper, a novel flow visualization tool is developed to address these issues by employing a structure-enhanced motion estimator composed of a data term and a regularization term. Specifically, a statistical correlation descriptor is designed for the data term to improve the accuracy of motion estimation by enhancing both illumination robustness and matching discrimination. Inspired by the strong distinguishability of a structure-texture distribution in a local window, a structure-enhanced regularizer that considers the physical mechanism of fluid diffusion is introduced to capture different motion patterns, enhance prominent flow structures, and remove unnecessary ripples or textures caused by instable perturbation or noise. The experimental results demonstrate that our approach significantly outperforms current motion estimators in handling illumination changes and predicting complex fluid flows, and it also achieves state-of-the-art evaluation results on the public fluid flow datasets. Furthermore, the designed flow visualization tool successfully captures diverse motion patterns in Jupiter’s White Ovals, which is crucial for understanding the physical mechanisms behind their formation and sustenance. © 1991-2012 IEEE.

关键词： Motion estimation

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Iterative refinement of amplitude and phase in single-channel speech enhancement 15

Iterative refinement of amplitude and phase in single-channe...

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15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014

作者： Mowlaee, Pejman Watanabe, Mario Kaoru Saeidi, Rahim Signal Processing and Speech Communication Laboratory Graz University of Technology Austria Speech and Image Processing Unit School of Computing University of Eastern Finland Finland

While the state-of-the-art speech enhancement methods are focused on the modification of the noisy spectral amplitude, our recent findings demonstrate positive impact of incorporating the speech phase spectrum in speech enhancement. In this show and tell proposal, we demonstrate the recent progress towards utilizing the phase information in closed-loop iterative manner leading to the joint enhancement of amplitude and phase spectra. In this show and tell, we provide a demo where a recorded speech corrupted with noise is enhanced by an iterative refinement of amplitude and phase. The improvement in speech enhancement in various signal-to-noise ratios is justified by improved perceived speech quality as well as not degrading the speech intelligibility performance. Copyright © 2014 ISCA.

关键词： Speech enhancement

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Corona noise characteristics in high voltage PLC channel

Corona noise characteristics in high voltage PLC channel

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2003 IEEE International Conference on Industrial Technology, ICIT - Proceedings

作者： Suljanović, Nermin Mujčić, Aljo Zajc, Matej Tasič, Jurij F. Laboratory for Digital Signal Image and Video Processing Faculty of Electrical Engineering Ljubljana Trzaska 25 1000 Ljubljana Slovenia

The paper presents the algorithm for estimation of frequency and time characteristics of the corona noise in high voltage power-line carrier (PLC) communications. In the frequency domain corona noise is represented with power spectral density and with Gaussian noise voltage with variable root mean square (RMS) value in time domain. The analytic method for estimation of the corona noise appearing at the line terminals in frequency and time domain is given. Simulations results are compared with the measurements on actual 400 kV power line. © 2003 IEEE.

关键词： Electric lines

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Quality measures in the processing of high-contrast images

Quality measures in the processing of high-contrast images

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Advances in image Transmission II 1980

作者： Algazi, V.R. Ford, G.E. Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California DavisCA95616 United States

The use of image quality measures in the design of processing algorithms and equipment is a difficult task. Realistic and useful images are complex and far from the threshold conditions under which psychophysical measurements and models are obtained. For a class of processing algorithms, the image distortion is actually proportional to the image contrast. For these algorithms it appears possible to determine a worst case image and to establish fairly simple quality criteria. The basic components of such a quality measure are discussed and examples of application given. © 1980 SPIE. All rights reserved.

关键词： image quality

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Road Crack Acquisition and Analysis System Based on Mobile Robot and Deep Learning 11

Road Crack Acquisition and Analysis System Based on Mobile R...

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11th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021

作者： Zhu, Guijie Fan, Zhun Ma, Peili Huang, Wenning Ye, Zhihao Huang, Mingwei Li, Jiangli Jiang, Zhicheng Zhong, Zhuwei He, Weiyuan Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China

ISBN: (纸本)9781665425278

In this paper, a road crack acquisition and analysis system based on mobile robot and deep learning is proposed. First, a virtual reality technology-based omnidirectional mobile robot is developed to remotely collect detailed road crack images. Next, an image dataset including different kinds of crack images collected by the mobile robot is constructed and utilized for training and testing a deep convolutional neural network (DCNN) model. Following this, the trained model is used to identify and segment the crack images acquired from the robot, and to facilitate the inspector to know the road surface condition, crack information (crack length, crack width, and crack area) is obtained using an image processing method. Finally, the proposed system and method are applied to a campus road, which realizes the accurate acquisition and analysis of road crack information, thus demonstrating the feasibility and effectiveness of the proposed system and method. © 2021 IEEE.

关键词： Mobile robots

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Overview of EMG signal Preprocessing and Classification for Bionic Hand Control

Overview of EMG Signal Preprocessing and Classification for ...

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2022 IEEE Information Technologies and Smart Industrial Systems, ITSIS 2022

作者： Ayachi, Monaam Seddik, Hassene University of Tunis Riftsi Research Laboratory: Intelligent Robotics Reliability and Image Signal Processing Electrical Department Tunis Tunisia

ISBN: (纸本)9781665477017

This paper deals with the field of Biological signal especially one of the most used signals in the field of prosthetic devices, which is the EMG signal. After introducing this kind of signal, we will talk about different techniques used for preprocessing it in order to prepare it for classification tasks. We Will then overview different noises that affect those sensible type of signals, different techniques applied for filtering them and the useful envelope detection methods that can be applied on EMG. The next part of this paper will look at some famous feature extraction and classification techniques that proved themselves useful when dealing with classification tasks of biological signals. Finally, we will present the mechanical design of a multiarticulate multifunctional prosthetic hand, the promising classification results that can gives 98.3% and our perspectives. © 2022 IEEE.

关键词： Bionics

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Multiple-window anomaly detection for hyperspectral imagery

Multiple-window anomaly detection for hyperspectral imagery

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2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings

作者： Liu, Wei-Min Chang, Chein-I Remote Sensing Signal Image Processing Laboratory Dept. of CSEE University of Maryland Baltimore County United States

ISBN: (纸本)9781424428083

Anomaly detection is of particular interest in hyperspectral image analysis since many unknown and subtle signals which cannot be resolved by multispectral sensors can now be uncovered by hyperspectral imagers. More importantly, the signals of this type generally cannot be identified by visual assessment or prior knowledge and provide crucial and critical information for data analysis. Many anomaly detectors have been designed based on the most widely used anomaly detector developed by Reed and Yu, called RX detector (RXD). However, a key issue in making RX detector-like anomaly detectors successful is how to effectively utilize the information provided by the sample correlation, e.g., sample covariance matrix used by RXD. This paper develops a concept of designing anomaly detectors which includes RXD-like anomaly detectors as special cases. It is referred to as multiple-window anomaly detection (MWAD) which makes use of multiple windows with varying sizes to capture different levels of local spectral variations so that anomalous targets of various sizes can be characterized and interpreted by different window sizes. With this new MWAD, many interesting findings can be derived including the RXD-like anomaly detectors as its special cases. © 2008 IEEE.

关键词： Covariance matrix

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Can We Distinguish Genuine Minutiae from Imposter Minutiae 17

Can We Distinguish Genuine Minutiae from Imposter Minutiae

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17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2020

作者： Phromsuthirak, Krisada Areekul, Vutipong Faculty of Engineering Kasetsart University Kasetsart Signal Image Processing Laboratory Department of Electrical Engineering Bangkok10900 Thailand

ISBN: (纸本)9781728164861

we propose a novel method to differentiate genuine minutiae from impostor minutiae of an enhanced latent fingerprint. Because poor-quality latent fingerprints are deposited on uncontrolled backgrounds with noises, the imposter minutiae are incorrectly detected by a conventional fingerprint enhancement process. As a result, these imposter minutiae decrease identification performance. We introduce a histogram of the spectrum difference between the original latent fingerprint and its enhanced image. This new feature is suitable for distinguishing between genuineness and imposter. The minutiae set from the NIST SD27 latent fingerprint database is used as ground truth to evaluate the performance of the proposed method and the existing quality assessment methods. The experimental results show that the proposed method outperforms the current methods in terms of precision and F-measure. © 2020 IEEE.

关键词： image enhancement

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Detection of ultrasonic closer flaws using nonlinear signal processing

Detection of ultrasonic closer flaws using nonlinear signal ...

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7th European Conference on Noise Control 2008, EURONOISE 2008

作者： Benammar, A. Drai, R. Kechida, A. Guessoum, A. Image and Signal Processing Laboratory Welding and NDT Centre Route de Dely-Ibrahim Chéraga 16035 Alger Algeria

The ultrasonic flaw detection is an important problem in the nondestructive evaluation (NDE) of materials. In order to successfully detect and classify flaw echoes from high scattering grain echoes, an efficient and robust method is required. In this paper, a method using split-spectrum processing (SSP) combined with a neural network (NN) has been developed and applied on the ultrasonic signals to perform the detection of closer echoes. SSP can display signal diversity and is therefore able to provide the signal feature vectors for signal classification. The neural network (NN) performs highly complex nonlinear mapping by which signals can be classified according to their feature vectors. Therefore, the combination of SSP and NN (SSP-NN) presents a powerful technique for ultrasonic NDE. The SSP is achieved by using Gaussian bandpass filters. Then, an adaptive three layer neural network using a backpropagation learning process is applied to perform the classification processing of frequency diverse data. The SSP-NN method has been tested using both simulated and experimental ultrasonic signals, and the results show that SSP-NN has good sensitivity in the detection of ultrasonic closer flaws echoes drowned in the noise. Key word : Ultrasonic NDE, Nonlinear signal processing, SSP, Neural networks.

关键词： Bandpass filters

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Predefined-Time Consensus Tracking Control of Multi-Agent Systems With Resilience to Communication Link Attacks

Predefined-Time Consensus Tracking Control of Multi-Agent Sy...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Yani Liu, Yangyang Lu, Minyin Zou, An-Min College of Engineering Shantou University Shantou China Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Shantou China

ISBN: (纸本)9781665465335

With consideration of communication link attacks, the distributed predefined-time consensus control issue of multi-agent systems is studied. First, a distributed resilient predefined-time observer is introduced to obtain an exact estimation of the states of the leader within predefined time. Second, a predefined-time consensus control protocol is proposed. The rigorous proof demonstrates that all follower agents can reach a common state within predefined time. At last a numerical example is presented to show the effectiveness of the resilient predefined-time controller. © 2022 IEEE.

关键词： Multi agent systems

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