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A computational vision approach to image registration

A computational vision approach to image registration

引用

International conference on Pattern Recognition

作者： Q. Zheng R. Chellappa Signal and Image Processing Institute University of Southern California Los Angeles CA USA Department of Electrical Engineering Center for Automation Research University of Maryland College Park MD USA

Automatic image registration is important for many multiframe-based image analysis applications. In this paper, a computational vision approach is presented for the estimation of 2-D translation, rotation, and scale from two partially overlapping images. The approach has the following features: (1) an illuminant direction estimator is used to obtain an initial estimate of camera rotation; (2) feature points are located based on a Gabor wavelet model for detecting local curvature discontinuities; (3) estimation of rotation and translation is formulated as a linear problem; and (4) hierarchical coarse-to-fine matching is used. This results in a fast and novel algorithm that produces good results even when large rotations and scale changes have occurred between the two frames and the images are devoid of significant features. Several applications of the algorithm are presented.< >

关键词： Computer vision image registration Cameras Motion estimation Object detection image motion analysis Robustness Feature extraction Forward contracts Coordinate measuring machines

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The Coronary Atherosclerosis Detection: A Diagnostic Approach of Digital Electrocardiography image Interpretation

The Coronary Atherosclerosis Detection: A Diagnostic Approac...

引用

Data Science and Its applications (ICoDSA), International conference on

作者： Firna Yenila Yuhandri Okfalisa Information System Department Universitas Putra Indonesia YPTK Padang Indonesia Information Technology Department Universitas Putra Indonesia YPTK Padang Indonesia Universitas Islam Negeri Sultan Syarif Kasim Riau Indonesia

ISBN: (数字)9798350365351

ISBN: (纸本)9798350365368

Coronary Atherosclerosis is recognized as the predominant cause of Chronic Heart Failure. The standard diagnostic modality for Coronary Atherosclerosis involves echocardiography (ECO); however, the accessibility of such diagnostic equipment remains constrained within several healthcare facilities. Consequently, there is a demand for a more straightforward diagnostic approach, specifically through the utilization of Electrocardiography (ECG). This investigation endeavors to introduce an automated methodology for the detection of Coronary Atherosclerosis, enhancing the precision of ECG interpretation via digital imaging predicated on cardiac signal detection graphs obtained through this modality. The algorithm employed to delineate the ECG signal dynamics for the diagnostic identification of Coronary Atherosclerosis is the Continuous wavelet Transform (CWT). The application of CWT follows the execution of multiple pre-processing phases on the ECG signal graph, including image cropping to isolate the graph within the ECG and segmentation to eliminate background interference, thereby concentrating on the graph for subsequent analysis. This preprocessing facilitates the interpretative process through the CWT algorithm. The analysis proceeds with a classification phase employing a Convolutional Neural Network (CNN), which differentiates between normal patient conditions and those presenting with Coronary Atherosclerosis and normal ECG. The experimental outcomes derived from the application of the proposed algorithm demonstrate a significant enhancement in the accuracy of ECG interpretation, achieving a diagnostic accuracy rate of 96% for the detection of Coronary Atherosclerosis.

关键词： image segmentation Continuous wavelet transforms Accuracy Echocardiography Heuristic algorithms Atherosclerosis Electrocardiography

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Indexing spatial content of still texture in MPEG-4

Indexing spatial content of still texture in MPEG-4

引用

European signal processing conference (EUSIPCO)

作者： Jayank Bhalod V Mohammed Zubair S. Panchanathan Visual Computing and Communications Laboratory Department of Computer Science and Engineering Arizona State University Tempe - Arizona USA

There has been a rapid increase in audio-visual information in digital form with the ever-increasing popularity of the Internet. The Moving Pictures Expert Group has recently presented a video compression and content manipulation standard, called MPEG-4 [1]. This was developed in response to the growing need for a coding method that can facilitate access to visual objects in natural and synthetic moving pictures in a wide variety of applications. In this paper, we propose a method for indexing the spatial content of Still Texture in MPEG-4 Video. There has been a number of approaches proposed recently [1],[3],[5],[6], which address content based indexing using features such as, color, shape and/or texture. We note that the still texture information is encoded using wavelet Transform in MPEG-4. Since still texture can have an arbitrary shape, we propose to employ a combination of shape, color and texture features. The shape features are derived from the alpha plane and represented using Cubic B-spline approximation. The color and texture features are extracted directly from the wavelet compressed domain. An important attribute of the proposed approach is also the introduction of the novel concept of “containment” of spatial features for content based indexing.

关键词： Shape image color analysis Transform coding Indexing Splines (mathematics) Feature extraction Vectors

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Scalable coding and progressive transmission of concentric mosaic using nonlinear filter banks

Scalable coding and progressive transmission of concentric m...

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IEEE International conference on image processing

作者： King-To Ng Shing-Chow Chan Heung-Yeung Shun Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong China Microsoft Research Limited USA

ISBN: (纸本)0780367251

This paper studies the scalable coding and progressive transmission of concentric mosaic to support interactive applications over a LAN or the Internet. Concentric mosaic is an effective 3D image based representation of a static scene. A typical concentric mosaic might consist of thousands of images, which poses significant problem in digital storage and transmission. A new multiresolution decomposition for supporting progressive transmission of a concentric mosaic is proposed. Instead of using the popular 9/7 wavelet filterbank, a nonlinear perfect reconstruction filter bank with lower arithmetic complexity is employed. It also considerably simplifies the random access operation of the slit images during rendering. By encoding the subband signals into different layers, a scalable compressed bit stream of the concentric mosaic is obtained. Therefore, progressive transmission of concentric mosaic, using a combination of these layers, to support devices with different capabilities become possible.

关键词： image storage Filter bank Local area networks Internet Layout signal resolution image reconstruction Arithmetic Rendering (computer graphics) Encoding

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A Review on Digital image Watermarking Using Transformation and Optimization Techniques

A Review on Digital Image Watermarking Using Transformation ...

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International conference on Advances in Computing, Communication Control and Networking (ICACCCN)

作者： Lalita Verma Sanjay Pratap Singh Chauhan School of Computer Science and Engineering Galgotias University Greater Noida India

ISBN: (数字)9781728183374

ISBN: (纸本)9781728183381

Now-a-days multimedia data is being generated very frequently in text format, image format, audio format etc. Security is the major issue of the multimedia data. Multimedia data can be very easily modified by the intruders. By using Watermarking and Steganography techniques the multimedia data can be protected from unauthorised access. Watermarking technique hides the data in the carrier signal. In the process of Steganography, the digital data (e.g. digital files like audio, video, text etc) can be embedded into some other digital file. The concept of watermarking is to keep the watermark robust from various attacks. Whenever the intruder tries to temper with the digital signal and removes the watermark, the digital data becomes useless as the quality is degraded. This paper discusses about various applications of watermarking, characteristics of Watermarking and basics of image processing. This paper also provides a comprehensive study of available literature on digital image watermarking. Some of the optimization techniques have also been discussed.

关键词： wavelet transforms Digital images image processing Watermarking Streaming media Optimization

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Digital image Watermarking Using Multilevel wavelet Decomposition and Human Visual System

Digital Image Watermarking Using Multilevel Wavelet Decompos...

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International conference on Information Science and applications (ICISA)

作者： Zahoor Jan Muhammad Khalid Anwar M. Mirza Fouzia Jabeen Almas Abbasi Zabie Tarin Alwina Durrani Department of Computer Science Abdul Wali Khan University Mardan Pakistan Department of Computer Science Government College of Management Sciences Peshawar Pakistan Department of Computer Engineering College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Shaheed Benazir Bhutto Women University Peshawar Pakistan Faculty of computer Science and information Technology University of Malaya Malaysia

In this modern world Digital watermarking is of prime importance. This has increased the demand for copyright protection. Digital watermarking is a solution to the problem of copyright protection and authentication of multimedia data while working in a networked environment. In this paper a non-blind watermarking has been proposed that embed a randomly generated binary numbers as watermark. Human Visual System (HVS) has been used to embed the watermark below the detection threshold (JND). High quality of robustness and imperceptibility are achieved through Just Noticeable Difference (JND) base selection of the detail coefficients. The experimental results show that the proposed technique is more resistant against all types of common signal processing operations and geometric attacks.

关键词： Watermarking Robustness Low pass filters image coding Discrete wavelet transforms

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Denoising one-dimensional signals with curvelets and contourlets

Denoising one-dimensional signals with curvelets and contour...

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IEEE National conference on Aerospace and Electronics (NAECON)

作者： Ryan Moore Soundararajan Ezekiel Erik Blasch Kate Gleason College of Engineering Rochester Institute of Technology Rochester NY Computer Science Indiana University of Pennsylvania Indiana PA Information Directorate Air Force Research Laboratory Rome NY

Fast Fourier Transforms (FFTs) and Discrete wavelet Transformations (DWTs) have been routinely used as methods of denoising signals. DWT limitations include the inability to detect contours, curves and directional information of multi-dimensional signals. In the past decade, two new approaches have surfaced: curvelets, developed by Candès; and contourlets, developed by Do et al. The typical applications of contourlets and curvelets include two-dimensional image data denoising. We explore the use of curvelets and contourlets to the one-dimensional (1D) denoising problem. Working with seismic data, we introduce various types of data noise and the wavelet, curvelet, and contourlet transforms are applied to each signal. We tested multiple decomposition levels and different thresholding values. The benchmark for determining the effectiveness of each transform is the peak signal-to-noise ratio (PSNR) between the original signal and the denoised signal. The proposed denoising methods demonstrate contourlets and curvelets as a viable alternative to the DWT and FFT during signal processing. The initial results indicate that the contourlet and curvelet methods yield a higher PSNR and lower error than the DWT and FFT for 1D data.

关键词： Discrete wavelet transforms PSNR Noise reduction Measurement

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Atmospheric correction of remotely sensed multispectral satellite images in transform domain

Atmospheric correction of remotely sensed multispectral sate...

引用

International conference on Advanced Computing, ICAC

作者： S. Gandhimathi Usha S. Vasuki Gowri Ariputhiran Velammal College of Engineering and Technology Madurai Tamil Nadu IN Department of ECE Velammal College of Engineering and Technology Madurai India

Remote sensing data provides much essential and critical information for monitoring many applications such as change detection, image fusion and land cover classification. Remotely sensed images are degraded due to the atmospheric effects. The atmospheric correction is one of the important pre processing steps to extract full spectral information from the remotely sensed images. In this paper, transform domain approaches are presented for the removal of atmospheric influences. Soft thresholding technique is adopted in wavelet transform method and gaussian high pass filter is used in homomorphic filtering. The results are tested on Landsat image consisting of 7 multispectral bands and their performance is evaluated using visual and statistical measures. The comparative analysis is done based on statistical parameters such as mean square error (MSE), peak signal to noise ratio (PSNR). Our result shows that wavelet transform is better for the removal of atmospheric effects than homomorphic filtering.

关键词： Discrete wavelet transforms Filtering Remote sensing Atmospheric waves Satellites PSNR

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Improving in Spectral Resolution for Closely-Spaced Targets Based on MUSIC Algorithm

Improving in Spectral Resolution for Closely-Spaced Targets ...

引用

International conference on Artificial Intelligence and image processing(ICAIIP’2012);International conference on Innovations in Electrical and Electronics Engineering(ICIEE’2012);International conference on Mechanical,Automobile and Biodiesel Engineering(ICMABE’2012);International conference on History,Literature and Management(ICHLM’2012);International conference on Agriculture,Chemical and Environmental Sciences(ICACES’2012);International conference on Biological and Medical applications(ICBMA’2012)

作者： M.Pourahmadi Department of Electrical Engineering Yazd branchIslamic Azad University

The multiple signal classification (MUSIC) method is severely based on the number of singular values of a multistatic response matrix (or signal subspace rank).In this paper we show that in the presence of multiple scattering between the targets,some singular values will greatly decrease and combine with the noise ones,so the performance of the most popular MUSIC methods degrades and even fails to estimate closely spaced target locations because of a reduction in signal *** such a case,we introduce a method to eliminate ambiguity in determining the number of scatterers employing a pre-processing step by two methods:discrete stationary wavelet transform (DSWT) and empirical mode decomposition (EMD).The DSWT is developed on the basis of features of the reflection coefficient between the *** application of this algorithm to measurement data,shows its superiority over the *** results indicate that MUSIC+DSWT yields accurate estimation of the target locations,even when there exist considerable noise and multiple scattering in the received signal.

关键词： MUSIC algorithm,wavelet transform,spectral resolution,microwave imaging.

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An efficient VLSI architecture for 2-D dual-mode SMDWT

An efficient VLSI architecture for 2-D dual-mode SMDWT

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IEEE International conference on Networking, Sensing and Control

作者： Chih-Hsien Hsia Jen-Shiun Chiang Shih-Hao Chang National Taiwan University of Science and Technology Taipei TW Tamkang University Taipei TW National Taiwan University Taipei TW

ISBN: (纸本)9781467351980

In this paper, we propose a highly efficient VLSI architecture for 2-D dual-mode (supporting 5/3 and 9/7 lifting-based) Symmetric Mask-based Discrete wavelet Transform (SMDWT) to improve the critical issue of the 2-D Lifting-based Discrete wavelet Transform (LDWT), and then obtains the benefit of low-latency reduced complexity, and low transpose memory. The SMDWT also has the advantages of reduced complexity, regular signal coding, short critical path, reduced latency time, and independent subband coding processing. The transpose memory requirement of the N×N is 9N. The architecture is based on the parallel and folding scheme processing to achieve higher hardware utilization ratio and reduce the silicon area. It is suitable for Very Large Scale Integration (VLSI) implementation and can be applied to real-time operating of computer vision applications.

关键词： Discrete wavelet transforms CMOS integrated circuits CMOS technology Very large scale integration Irrigation Biomedical imaging image recognition

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