检索结果-内蒙古大学图书馆

International Conference on image and signal processing and their applications (ISPA)

作者： Mohamed CHOUAI Mostafa MERAH José-Luis SANCHO-GOMEZ Malika MIMI Signals and systems laboratory Mostaganem University Mostaganem Algeria TDAM Research Group (Data Processing and Machine Learning) Information and Communications Universidad Politécnica de Cartagena Cartagena Murcia Spain

ISBN: (纸本)9781728131573

Billions of suitcases and other belongings are checked every year in airport X-ray systems around the world. This process is very important because it involves the detection of potentially dangerous objects such as firearms and explosives. However, the image quality of x-ray screening devices needed to be improved. This article attempts to make a contribution to the field of improving the radiographic image of luggage by proposing a complete procedure for improving the image quality based on discrete wavelet transform (DWT) image fusion followed by a noise suppression operation to obtain a good improvement of the fusion result. This article also presents a comparative analysis of five well-known image enhancement algorithm models, the evaluation is done using the Peak signal-to-Noise Ratio (PSNR). The results show that the proposed system provides promising results compared to the other techniques tested, which proves that the proposed approach is very appropriate and recommended for easy / fast identification of threatening objects in a manual or automatic manner.

关键词： Transport security Baggage control image enhancement Fusion wavelet transform Fusion reactions image enhancement Fusion, biological image quality wavelet transforms Airports FUSION fusion (melting) discrete wavelet transform image enhancement algorithm Peak signal-to-noise ratio Firearms double energy

来源：评论

学校读者我要写书评

暂无评论

Digital image interpolation in Matlab® / First edition.

引用

2019年

作者： Kok Chi-Wah

来源：内蒙古大学图书馆图书评论

学校读者我要写书评

暂无评论

Natural image Deblurring using Recursive Deep Convolutional Neural Network (R-DbCNN) and Second-Generation wavelets

Natural Image Deblurring using Recursive Deep Convolutional ...

引用

IEEE International Conference on signal and image processing applications (ICSIPA)

作者： Asem Khmag Noraziahtulhidayu Kamarudin Faculty of Engineering University of Zawia Az zawia Libya School of Computing & Creative University College of Technology Sarawak Sarawak Malaysia

Deconvolution in blind digital images is a common issue in image enhancement techniques, which basically was a notion of many researches. In this study, spatial varying blind deconvloution is stated and implemented. In addition, image noise removal approach which utilizes the normalized platform of second-generation wavelet transform is applied as pre-processing step. The low and high frequencies are decomposed in this step in order to be extracted. Practically, the main merit of wavelet transform is its efficiency in reduction of data redundancy in digital images. This feature helps a lot in terms of data classification where it is easy to distinguish the signal from its noisy counterpart. The second step, a recursive deep convolutional neural network (R-DbCNN) is implemented to suppress any image blur affected by second-generation wavelet transform to further remove the blur of noisy image. The experimental results depict that the suggested method outperforms recent blur removal techniques for different bluer image types in terms of image quality and time consumption.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Parallel Strategies for 2-D Lifting wavelet Transform Using GPU

A Parallel Strategies for 2-D Lifting Wavelet Transform Usin...

引用

International Congress on image and signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Lei Wang Hongying Liu Li Sun Mei Zhou Quanjie Zhuang Shanghai Key Laboratory of Multidimensional Information Processing Communications and Electronic Engineering Institute East China Normal University Shanghai China Shanghai Lanche Biological Technology Co. Ltd. Shanghai China

Lifting wavelet Transform has a huge number of applications in image-processing techniques, it has been applied in field like image compression, fusion, de-noising, et al, but for large scale image, the algorithm is too slow to meet the real-time requirements. To solve this problem, this work proposed a parallel strategy based on GPU for 2-D lifting wavelet transform. Through the performance test and analysis, the proposed lifting scheme achieve considerable speedups compared with CPU version for the same image size.

关键词： Instruction sets Kernel Graphics processing units Discrete wavelet transforms Synchronization

来源：评论

学校读者我要写书评

暂无评论

Multi-level Stress Assessment Using Multi-domain Fusion of ECG signal

Multi-level Stress Assessment Using Multi-domain Fusion of E...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Zeeshan Ahmad Naimul Mefraz Khan Department of Electrical and Computer Engineering Ryerson University Toronto ON Canada

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a burning research topic in biomedical signal processing. However, existing literature provides only binary assessment of stress, while multiple levels of assessment may be more beneficial for healthcare applications. Furthermore, in present research, ECG signal for stress analysis is examined independently in spatial domain or in transform domains but the advantage of fusing these domains has not been fully utilized. To get the maximum advantage of fusing different domains, we introduce a dataset with multiple stress levels and then classify these levels using a novel deep learning approach by converting ECG signal into signal images based on R-R peaks without any feature extraction. Moreover, We made signal images multimodal and multi-domain by converting them into time-frequency and frequency domain using Gabor wavelet transform (GWT) and Discrete Fourier Transform (DFT) respectively. Convolutional Neural networks (CNNs) are used to extract features from different modalities and then decision level fusion is performed for improving the classification accuracy. The experimental results on an in-house dataset collected with 15 users show that with proposed fusion framework and using ECG signal to image conversion, we reach an average accuracy of 85.45%.

关键词： Stress Electrocardiography Feature extraction Machine learning Discrete Fourier transforms Time-frequency analysis

来源：评论

学校读者我要写书评

暂无评论

Multi-level stress assessment using Multi-domain fusion of ECG signal

arXiv

引用

arXiv 2020年

作者： Ahmad, Zeeshan Khan, Naimul Mefraz Department of Electrical and Computer Engineering Ryerson University 350 Victoria St TorontoONM5B 2K3 Canada Department of Electrical and Computer Engineering Ryerson University 350 Victoria St TorontoONM5B 2K3 Canada

Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a burning research topic in biomedical signal processing. However, existing literature provides only binary assessment of stress, while multiple levels of assessment may be more beneficial for healthcare applications. Furthermore, in present research, ECG signal for stress analysis is examined independently in spatial domain or in transform domains but the advantage of fusing these domains has not been fully utilized. To get the maximum advantage of fusing diferent domains, we introduce a dataset with multiple stress levels and then classify these levels using a novel deep learning approach by converting ECG signal into signal images based on R-R peaks without any feature extraction. Moreover, We made signal images multimodal and multidomain by converting them into time-frequency and frequency domain using Gabor wavelet transform (GWT) and Discrete Fourier Transform (DFT) respectively. Convolutional Neural networks (CNNs) are used to extract features from different modalities and then decision level fusion is performed for improving the classification accuracy. The experimental results on an in-house dataset collected with 15 users show that with proposed fusion framework and using ECG signal to image conversion, we reach an average accuracy of 85.45%. Copyright © 2020, The Authors. All rights reserved.

关键词： Discrete Fourier transforms

来源：评论

学校读者我要写书评

暂无评论

Satellite image Band Registration with Dynamic Time Warping and Discrete wavelet Transform 26

Satellite Image Band Registration with Dynamic Time Warping ...

引用

26th IEEE signal processing and Communications applications Conference (SIU)

作者： Ufuk, D. Utku Acikgoz, Ibrahim S. Teke, Mustafa Ozbayoglu, A. Murat TUBITAK Uzay Teknol Arastirma Enstitusu Ankara Turkey TOBB ETU Bilgisayar Muhendisligi Bolumu Ankara Turkey

ISBN: (纸本)9781538615010

Due to the imperfect physical arrangement of camera sensors, spectral bands of ground observation satellite images are usually shifted relative to each other. In order to address this issue, we propose a computationally simple band registration method which is based on Dynamic Time Warping (DTW) and Discrete wavelet Transform (DWT) algorithms. This method has been tested on 10 frames of GOKTURK-2 images and compared to a Scale-Invariant Feature Transform (SIFT) based method. In terms of quality, the proposed method have yielded very close results compared to SIFT.

关键词： satellite image image processing band registration dynamic time warping discrete wavelet transform

来源：评论

学校读者我要写书评

暂无评论

Pavement images Denoising with Cracks Detection and Classification Using 2D Discrete wavelet Transform and Savitzky-Golay Filters

Pavement Images Denoising with Cracks Detection and Classifi...

引用

IEEE International Conference on signal and image processing applications (ICSIPA)

作者： Zoubir Hamici Turki I. Al-Suleiman Obaidat Al-Zaytonnah University of Jordan Amman Jordan

image processing has gained an increased usage and impact in modern pavement networks automatic distress severity classification (DSC). DSC defines priorities and maintenance resources optimum allocation in order to achieve a cost-effective rehabilitation process. This paper presents a novel computer vision algorithm having the ability to process, isolate and evaluate the distress severity level of a pavement. A pavement color image is converted to grayscale and then processed for image denoising of the granularity and complex texture that represent and artifact in cracks edge detection. The processing is achieved by a 2D dual-tree double density wavelet transform filter banks that significantly reduces the granularity noise while preserving the pavement cracks for edge detection. The 2D wavelet FIR filters perform analysis, soft thresholding then a synthesis of the image. The second step is then an edge detection process followed by morphological filtering and labeled components size-histogram filter to isolate false edges as residuals of denoising. A final step is performed by two Savitzky-Golay filters for the detection of longitudinal and transverse alligator cracks projections. A weighted score function with multiple parameters is used for DSC.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Vibration signal Analysis for Bearing Fault Diagnostic of Asynchronous Motor using HT-DWT Technique

Vibration Signal Analysis for Bearing Fault Diagnostic of As...

引用

International Conference on image and signal processing and their applications (ISPA)

作者： Sara Seninete Malika Mimi Bilal Djamal eddine Cherif Abdelazziz Ould Ali dept. Electrical Engineering University Abdel Hamid Ibn Badis of Mostaganem Mostaganem Algeria dept. Electrical Engineering University of science and Technology of Oran Oran Algeria

ISBN: (纸本)9781728131573

Nowadays, fault detection in induction motors has gained importance. Motor health monitoring is performed to diagnose their operating condition using vibration signals. These signals are processed using different signal processing methods to extract the characteristic parameters permitting localization of the fault. In this paper, we propose a diagnostic method based on Hilbert and Discrete wavelet Transforms for the detection of bearing faults in asynchronous machines. The discrete wavelet transform (DWT) is intended to provide the detail coefficients while the Hilbert transform (HT) is used to obtain the temporal envelope then the envelope spectrum of the detail. The kurtosis value indicates the optimum decomposition wavelet level containing the significant frequencies corresponding to faults for early detection. The result obtained by HT-DWT is more suitable for the analysis of emergency signals. This technique is effective for either stationary or nonstationary signals. Healthy case is compared to faulty case in order to extract frequencies characterizing different faults. The validation of this approach is evaluated by comparing theoretical with experimental results.

关键词： Vibration Inner race Outer race Detail Envelope spectrum outer race Vibration Asynchronous motors signal analysis discrete wavelet transform faults Fault diagnosis Hilbert

来源：评论

学校读者我要写书评

暂无评论

A Review of Motion Segmentation: Approaches and Major Challenges

A Review of Motion Segmentation: Approaches and Major Challe...

引用

International Multidisciplinary Information Technology and Engineering Conference (IMITEC)

作者： Jana Mattheus Hans Grobler Adnan M. Abu-Mahfouz University of Pretoria South Africa Council for Scientific and Industrial Research South Africa

ISBN: (数字)9781728195209

ISBN: (纸本)9781728195216

Motion segmentation has applications in, amongst others, robotics, traffic monitoring, sports analysis, inspection, video surveillance, compression, and video indexing. However, the performance of most methods is limited compared to human capabilities. Based on extensive literature the following challenges remain: occlusions, temporary stopping, missing data, and segmenting multiple objects. In this paper, several popular and state-of-the-art methods were reviewed, with the focus on the most important attributes. These methods were classified according to the main approach taken, namely image Difference, Optical Flow, wavelet, Statistical, Layers, Manifold Clustering, Template Matching, and Deep Learning. The investigated methods are compared and major research challenges are highlighted. Based on the review, improvements are identified as a basis for future research.

关键词： Manifolds Computer vision Motion segmentation Video surveillance Trajectory Video signal processing Sports

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：