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Proceedings of the 2020 4th International conference on Vision, image and signal processing

作者： Seyed Vahid Mirnezami Ali HamidiSepehr Mahdi Ghaebi Seyed Reza Hassan-Beygi Colaberry Incorporated Boston MA USA Agricultural Engineering Department University of Tehran Iran

ISBN: (纸本)9781450389532

Apricot which is a cultivated type of Zerdali (wild apricot) has an important place in human nutrition and its medical properties are essential for human health. the objective of this research was to obtain a model for apricot mass and separate apricot variety with image processing technology using external features of apricot fruit. In this study, five verities of apricot were used. In order to determine the size of the fruits, three mutually perpendicular axes were defined, length, width, and thickness. Measurements show that the effect of variety on all properties was statistically significant at the 1% probability level. Furthermore, there is no significant difference between the estimated dimensions by image processing approach and the actual dimensions. the developed system consists of a digital camera, a light diffusion chamber, a distance adjustment pedestal, and a personal computer. images taken by the digital camera were stored as (RGB) for further analysis. the images were taken for a number of 49 samples of each cultivar in three directions. A linear equation is recommended to calculate the apricot mass based on the length and the width with R2 = 0.97. In addition, ANFIS model with C-means was the best model for classifying the apricot varieties based on the physical features including length, width, thickness, mass, and projected area of three perpendicular surfaces. the accuracy of the model was 87.7.

关键词： Apricot image processing Classification Machine Learning

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A Computer-aided Method for Sleep Stage Scoring Employing Single Channel Electroencephalogram signal

A Computer-aided Method for Sleep Stage Scoring Employing Si...

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International conference on Electrical Information and Communication Technology (EICT)

作者： Arpita Das Tahia Tasnim Naqib Sad Pathan Quazi Delwar Hossain Electrical and Electronic Engineering Chittagong University of Engineering and Technology Chattogram Bangladesh

ISBN: (数字)9781728160405

ISBN: (纸本)9781728160412

An automatic sleep monitoring system is a prime requirement in order to minimize analysts' workload of visually inspecting large-scale data for sleep scoring and to improve the accuracy at large range. this research introduces a robust, precise single channel EEG-based automated classification scheme for sleep states based on Variational Mode Decomposition (VMD). After pre-processing and decomposition, various features are obtained from the decomposed modes and the pre-processed EEG signal. this proposed method aims to use VMD for the first time in EEG based sleep scoring to the best of our knowledge. Our model achieved its best performance using 10-fold cross-validation in RF classifier after enormous experimentation. Our model yielded promising classification performances of 98.1894%, 95.4183%, 93.2352%, 92.0181% and 90.8283% overall accuracy for 2-states to 6-states classification respectively. this scheme also shows a high or comparable detection accuracy for awake, S1, S2, S3 and REM stages of 5-stage sleep scoring.

关键词： Sleep Electroencephalography Feature extraction Brain modeling Radio frequency Sensitivity Discrete wavelet transforms

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An Efficient Method for the Unmanned Aerial Vehicle image Denoising

An Efficient Method for The Unmanned Aerial Vehicle Image De...

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2013 IEEE 4th International conference on Electronics Information and Emergency Communication

作者： Fang Liu Zhiren Deng College of electronic information and control engineering Beijing University of Technology

ISBN: (纸本)9781467349345

An efficient method for the unmanned aerial vehicle (UAV) image denoising is proposed by combining an adaptive wavelet thresholding denoising and the image enhancement method in this paper. this method is aimed at improving the effect of the wavelet thresholding denoising method and enhancing the edge of the image. An adapti ve threshold value which changes with the change of the decomposition scale and the direction of the subband is selected for denoising. After wavelet denoising, the image enhancement method is used for enhancing the edge of the image. Experimental results show that, compared with the other methods, the proposed method yields bigger peak signal-to-noise ratio and superior visual image quality-measured by universal image quality index. It also retains more edges and details of the image.

关键词： unmanned aerial vehicle (UAV) adaptive wavelet thresholding denoising image enhancement

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3D Object Reconstruction Using Sequentially Activated Multiple Depth Cameras

3D Object Reconstruction Using Sequentially Activated Multip...

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IEEE signal processing and Communications applications (SIU)

作者： Esra Tunçer Şevket Gümüştekin İzmir Yüksek Teknoloji Enstitüsü İzmir Türkiye

ISBN: (数字)9781728172064

ISBN: (纸本)9781728172071

In this study, 4 depth cameras (Kinect v1) were placed around the object in order to obtain the 3-dimensional structure of an object. Computer bandwidth and interference problems encountered during the operation of multiple Kinects were solved with additional USB 2.0 controllers and electronic shutters. Calibration was performed on infrared images to merge the acquired images. Alignment problems were solved by the Iterative Closest Point method and an alignment with 3.41% error rate was obtained. Poisson Surface Reconstruction was implemented in Meshlab software for 3D modeling objects with different geometrical characteristics.

关键词： Universal Serial Bus Cameras three-dimensional displays Calibration Surface reconstruction Interference image reconstruction

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Assessment of cardiac time intervals by wavelet transform of the impedance cardiogram

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TECHNOLOGY AND HEALth CARE 2016年第Suppl 2期24卷 S803-S809页

作者： Stepanov, Rodion Podtaev, Sergey Dumler, Andrey Chugainov, Sergey Inst Continuous Media Mech Ak Korolev Str 1 Perm 614013 Russia Perm State Med Acad Dept Intro Internal Dis Perm Russia

BACKGROUND: Impedance cardiography (ICG) is an inexpensive, noninvasive technique for estimating hemodynamic parameters. ICG can be used to obtain the ejection fraction of the left atrium and to monitor systolic time intervals. Traditional ICG technique does not enable unambiguous detection of the left ventricle ejection time (LVET) and the time relationships between specific marker points. OBJECTIVE: this work aims to approbate a new approach for ICG signal processing using wavelet transform (WT) and to investigate the possibilities of this approach for determination of the parameters which are related to the stroke volume (SV), in particular LVET. MEthODS: thoracic tetrapolar polyrheocardiography method for simultaneous registration of ECG, ICG and phonocardiograms has been used. A control group consisted of eight healthy men aged 20-25 years. In addition, four patients with essential hypertension participated in the study. wavelet representation of the ICG data produced local maxima in a two dimensional distribution of the wavelet coefficient. Each extremum point was characterized by the amplitude, scale and time, which determine SV. RESULTS: LVET was defined as the scale corresponding to the E-wave maximum related to the systolic phase of the cardiac cycle. Also, we defined the initial systolic time interval (ISTI) as the time interval between R peak in the ECG and E-wave maximum on the wavelet plane. During functional test LVET and ISTI values defined by WT demonstrated a proper hemodynamic response to loading for the control group and patients with essential hypertension. CONCLUSION: the proposed approach demonstrates the ability of ICG-WT technique for adequate assessment of SV parameters, including cardiac time intervals.

关键词： Impedance cardiography wavelet transform hemodynamic parameters

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the applications of the new Chinese Remainder theorems for three moduli sets

The applications of the new Chinese Remainder Theorems for t...

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Canadian conference on Electrical and Computer Engineering (CCECE)

作者： Wei Wang M.N.S. Swamy M.O. Ahmad Yuke Wang Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

In this paper, we apply the New Chinese Remainder theorem I (New CRT-I) to design the residue-to-binary converters for all the recently introduced three moduli sets M/sub 1/={22/sup n/+1,2/sup n/+1,2/sup n/-1}, M/sub 2/={2/sup n/,2/sup n/-1,2/sup n-1/-1}. M/sub 3/={2/sup n/,2/sup n/+1,2/sup n/-1}, and M/sub 4/=(2n, 2n+1, 2n-1). For all these moduli sets, the converters based on the New CRT-I are consistently faster and require less hardware, compared to the previous residue-to-binary converters which are designed based on the traditional Chinese Remainder theorem.

关键词： Cathode ray tubes Hardware Digital arithmetic image converters Dynamic range Application software signal processing signal design Digital signal processing Fast Fourier transforms

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Automated Condition Monitoring Using Artificial Intelligence 2020

Automated Condition Monitoring Using Artificial Intelligence

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Proceedings of the 2020 4th International conference on Vision, image and signal processing

作者： Ieuan Griffiths University of South Wales Treforest Pontypridd UK

ISBN: (纸本)9781450389532

Machine maintenance is a major part of total operating costs for manufacturing and production plants, hence, having a cost-effective maintenance strategy is key to success. Most standard solutions operate on a time-driven approach where repairs or replacements are carried out after a given amount of time. this results in healthy machines being replaced unnecessarily incurring losses in both time, resource, and parts. Predictive maintenance utilises sensors capable of collecting real-time operating data and analytical techniques to predict when a machine will require maintenance. this research develops a vibration analysis tool that can detect and differentiate a machines operating conditions without any human analysis or intervention demonstrated via a case study. By using spectrograms in conjunction with image recognition and unsupervised learning, the tool is capable of being applied to many different machines without modification. Results show that features extracted using convolutional auto-encoding and t-SNE, are capable of being clustered in an unsupervised manner accurately based on case study test conditions. Future work looks at the application of this tool into a real-time data stream that can determine operating conditions in real-time.

关键词： signal processing Condition monitoring Predictive maintenance Unsupervised learning Machine learning Neural networks Artificial intelligence Machine maintenance Fault detection

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Robot Control Using an Inexpensive P300 Based BCI

Robot Control Using an Inexpensive P300 Based BCI

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Iranian conference of Biomedical Engineering (ICBME)

作者： Shafie Bahman Mohammad B. Shamsollahi Biomedical Signal and Image Processing Laboratory (BiSIPL) Sharif University of Technology Tehran Iran

ISBN: (数字)9781728156637

ISBN: (纸本)9781728156644

Brain Computer Interfaces (BCI) are an important concept of biomedical engineering because of their ability to improve life conditions for people with different disabilities. Lots of studies have worked on important characteristics of BCI systems, such as speed and accuracy, whereas price is an important aspect too. thus, a low cost BCI system with high accuracy clearly can help more people. Our purpose in this study is to design a P300 based BCI system using a low-priced EEG headset which has an acceptable accuracy. Our final design got a mean real-time accuracy of 93.3% which is comparable to systems with much more expensive hardware.

关键词： Electroencephalography Robots Real-time systems Task analysis Graphical user interfaces Mathematical model Biomedical engineering

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Adaptive Compressive Sensing for Natural images Using Schur Decomposition and Optimized Reconstruction

Adaptive Compressive Sensing for Natural Images Using Schur ...

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Sustainable Expert Systems (ICSES), International conference on

作者： M. Aarthi Elaveini T. Deepa Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Ramapuram Chennai India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Compressive sensing (CS) is growing as an effective method for efficient imagine capture and recovery by harnessing the fundamental sparseness of natural images. the paper presents a unique framework for CS of live images employing Schur decomposition, a matrix decomposition approach that improves the detection and reconstruction processes. the suggested technique utilizes Schur decomposition to enhance the sensing matrix, facilitating more effective sampling by collecting essential imagine information in both spatial and frequency domains. the Schur-based sensing matrix, in contrast to conventional random sensing matrices, is designed to use the structural characteristics of real pictures, hence enhancing the precision of image reconstruction from a reduced quantity of observations. the integrated Schur decomposition with an iterative image reconstruction algorithm, incorporating Orthogonal Matching Pursuit (OMP) promotes sparsity. the combination improves the robustness of the recovery process while reducing reconstruction artifacts. Extensive simulations demonstrate that proposed Schur-based framework achieves superior performance compared to conventional CS techniques, particularly in terms of Peak signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM). the proposed method improves the quality of reconstructed images and expedites the convergence of the reconstructing technique, hence reducing computational complexity. the framework is assessed over several natural imagine datasets, demonstrating substantial improvements in image quality and computing efficiency resulting in a PSNR of 37.263 dB and SSIM 0.813 for CAT image. the Schur decomposition method for CS is an effective solution for applications necessitating quick picture capture and high-quality reconstruction, including medical imaging, remote sensing, and real-time image processing systems.

关键词： image quality PSNR Matching pursuit algorithms Real-time systems Iterative algorithms Sensors Matrix decomposition image reconstruction Compressed sensing Remote sensing

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An adaptive threshold for change detection methods using a windowed entropy-based criterion - Application to fault-tolerant fusion in collaborative mobile robotics

An adaptive threshold for change detection methods using a w...

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conference on Control and Fault-Tolerant Systems (SysTol)

作者： Bilal Daass Denis Pomorski Kamel Haddadi Univ. Lille Signal et Automatique de Lille Lille France Univ. Lille UMR 8520- IEMN Lille France

ISBN: (纸本)9781728103815

Nowadays, process supervision occupies an important place in quality control, cooperative localization in mobile robotics, video and image processing, and intelligent system design, to name a few. Indeed, any failure of such processes can reduce performance and have serious consequences. the development of statistical methods, capable of detecting and locating anomalies in these dynamic systems as quickly as possible, is of real interest. In this context, we have proposed in a previous study a reformulation of the change detection strategy using an entropy-based criterion. Our approach allowed the calculation of an adaptive threshold, unlike the Bayes criterion. In this paper, we propose an improvement of this study by introducing the use of an optimal window of observations. We validate the proposed approach to the Exponentially Weighted Moving Average (EWMA) control charts, which is a commonly used change detection technique. Our strategy is illustrated on a well-known example of the literature. Finally, this windowed entropy-based criterion allows one to design a fault-tolerant fusion methodology, which is experimentally validated from an extended Kalman filter (EKF) in collaborative mobile robotics.

关键词： Microsoft Windows Robots Control charts Change detection algorithms Entropy Fault tolerant systems Collaboration

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