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International conference on Computer Vision (ICCV)

作者： B. Stenger V. Ramesh N. Paragios F. Coetzee J.M. Buhmann Department of Engineering University of Cambridge Cambridge UK Imaging & Visualization Department Siemens AG Corporate Research and Development Princeton NJ USA Institute for Computer Science II University of Bonn Germany

ISBN: (纸本)0769511430

Hidden Markov models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Their use involves an off-line learning step that is used as a basis for on-line decision making (i.e. a stationarity assumption on the model parameters). But, real-world applications are often non-stationary in nature. This leads to the need for a dynamic mechanism to learn and update the model topology as well as its parameters. This paper presents a new framework for HMM topology and parameter estimation in an online, dynamic fashion. The topology and parameter estimation is posed as a model selection problem with an MDL prior. Online modifications to the topology are made possible by incorporating a state splitting criterion. To demonstrate the potential of the algorithm, the background modeling problem is considered. Theoretical validation and real experiments are presented.

关键词： Hidden Markov models Topology Application software Parameter estimation signal processing algorithms State estimation Visualization Computer science Computer vision image analysis

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SoReNet: a novel deep network for audio surveillance applications

SoReNet: a novel deep network for audio surveillance applica...

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IEEE International conference on Systems, Man and Cybernetics

作者： Antonio Greco Alessia Saggese Mario Vento Vincenzo Vigilante Department of Computer Engineering Electrical Engineering and Applied Mathematics (DIEM) University of Salerno Via Giovanni Paolo II 132 Fisciano (SA) Italy

In the era of third generation surveillance systems, it becomes more and more useful to have available a solution able to automatically detect abnormal events. The interest for audio analysis is thus growing in the last years, due to the large amount of situations where a microphone and an audio surveillance system can be profitably used by the human operator in charge of control. In this paper, we propose a method for automatically analyzing the audio stream for surveillance purposes: it is able to detect the presence of abnormal events such as screams, gun shots and broken glasses. Instead than processing directly raw data (the audio signal), the stream is represented by means of an image, namely the spectrogram, a time-frequency representation of the audio stream. In this way, we formulate the problem of audio analysis as a problem of image classification. Thus, we propose to use a Convolutional Neural Network with the following two main properties: inspired by VGG network, we employed very small kernels in convolutional layers; furthermore, we adopted a pyramidal structure in fully connected layers. These choices allow to have good generalization capabilities of the network even in presence of a not so wide dataset. The performance, computed over a standard dataset already used for benchmarking purposes in the field of audio surveillance, confirms the effectiveness of the proposed approach.

关键词： Surveillance Spectrogram Streaming media Computer architecture Kernel Time-frequency analysis Convolution

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Recognition of Hybrid Digital Watermarking Techniques using Digital image processing using Deep Learning Techniques

Recognition of Hybrid Digital Watermarking Techniques using ...

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Augmented Intelligence and Sustainable Systems (ICAISS), International conference on

作者： Chilumala Indira RM Noorullah Praveen Kumar Balguri Sowjanya Krishna Pinisetty Department of Computer Science and Engineering Institute of Aeronautical Engineerring Dundigal Hyderabad India Department of Aeronautical Engineering Institute of Aeronautical Engineerring Dundigal Hyderabad India Institute of Fundamental and Frontier Science University of Electronic Science and Technology of China Chengdu China

Digital watermarking is the procedure to identify the source and creator of the data. This is a form of digital media marker such as video, audio or image format. It helps to protect the data from various external unauthorized access. This is done through embedded digital information in the carrier signal to identify ownership and copyright protection. Security and privacy concerns need to be improved due to the rapid increase in the transmission and receiving of digital data. Various sectors such as the navy, military, intelligence, and police are sending and receiving numerous data through online mode. The existing system utilizes Arnold map with QWT-DCT techniques which are unable to obtain invisibility in attack detection. To overcome the limitations of the existing system the proposed system is implemented. They are highly confidential and need to be secured and protected thus hybrid digital watermarking techniques such as nested forms of watermarking are employed. If the third parties tend to make any modification, then it is termed as an attack. The removal of digital watermarking by third parties through certain modifications are denoted through copyright protection application. For security applications and to avoid various types of attacks, Discrete wavelet Transform (DWT) and Non-sampled Contourlet Transform (NSCT) are employed. Security and privacy is obtained through the Quaternion Fourier Transform (QFT) based algorithm with human speech recognition. The pixel displacement with pixel encryption is enhanced to save the privacy of images. Digital watermarking requires security, robustness, watermarking keys and computational cost parameter. Thus to protect the data by neglecting various conventional attacks, digital watermarking techniques are implemented through deep convolutional neural networks.

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Removal of Gaussian Noise from Stationary image using Shift Invariant wavelet Transform

Removal of Gaussian Noise from Stationary Image using Shift ...

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International conference on Wireless and Optical Communications Networks

作者： Vikas Gupta Rajesh Mahle Ashish Shukla H.O.D. of ECE Dept. TIT Rajiv Gandhi Technical University Bhopal M.P. India ECE Dept. TIT Rajiv Gandhi Technical University Bhopal M.P. India

ISBN: (纸本)9781467359986

Discrete wavelet transform (DWT) has gained widespread recognition and popularity in image processing due to its ability of capturing energy of signal in a few energy transform value. As well as it has also ability to underline and represent time-varying spectral properties of many transient and other nonstationary signals. In DWT denoising is done only in detail coefficient, this offer advantage of smoothness and adaption. However DWT has a lack of shift invariance. This shift-variance is a major problem with the use of DWT for transient signal analysis and pattern recognition applications. Denoising of images with the DWT some time also give visual artifacts due to Gibbs phenomena in neighbourhood of discontinuities. In this paper, a shift-invariant analysis scheme is proposed for removing of additive Gaussian noise in stationary image. An investigation has been made on discrete wavelet transform with shift invariant in terms of PSNR and visual performance.

关键词： PSNR (Peak signal to noise ratio) DWT (Discrete wavelet transform) ε- Decimated Discrete wavelet Transform (ε- Decimated DWT) Shift Invariant wavelet transform

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Content Based image Retrieval by Combining Feature Vector

Content Based Image Retrieval by Combining Feature Vector

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International conference on Wireless Communications, signal processing and Networking

作者： S. D. Ruikar Rohit S. Kabade Electronics Engg Dept. Walchand College of Engineering Sangli India Electronics & Comm. Engg Dept PVPIT Budhgaon Sangli India

ISBN: (纸本)9781467393393

This paper describes the searching problem of images stored in big databases i.e. content based image retrieval (CBIR) system. It represents the behaviour and proposes solution for it. In general vast deployment in various applications therefore the capacity of image database increases because it's needed efficient CBIR method. This paper uses the primary image features like colour, shape and texture. This primary features take out using various algorithms those are useful to obtain similarity check into images. It describes the result using MATLAB software application, with a large image database. It utilizes feature of colour, texture and shape of the database images for comparison purpose and further for obtaining of image and it including relevance.

关键词： Color Shape Texture wavelet Etc

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Data Compression in Wireless Visual Sensor Networks using wavelets

Data Compression in Wireless Visual Sensor Networks using Wa...

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International conference on Wireless Communications, signal processing and Networking

作者： Shabir Ahmad Sofi Roohie Naaz Department of Information Technology National Institute of Technology Srinagar Hazratbal Kashmir India Department of Computer Science & Engineering National Institute of Technology Srinagar Hazratbal Kashmir India

ISBN: (纸本)9781467393393

Wireless Sensor Networking is a sensor information gathering technology that has a wide range of applications in numerous fields. However due to the fact that sensor nodes have limited battery and are deployed in remote and harsh environments, energy efficient and real time transmission of the information are still open challenges. Since in a wireless sensor network data transmission is the most power consuming task, so far most useful techniques for the purpose of energy efficient and real time transmissions are based on data compression, the majority of them are based on wavelet transform. This paper give performance analysis of different wavelets for energy efficient and real time image data transmission in application like environment monitoring using wireless visual sensor networks. The performance evaluation shows that Haar wavelet is better in terms of energy efficiency and transmission time.

关键词： Wireless Visual Sensor Network (WVSN) Discrete wavelet Transform (DWT) Skipped High-pass Sub-band (SHPS) Data Compression

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Distance Quantization Method for Fast Nearest Neighbor Search Computations with applications to Motion Estimation

Distance Quantization Method for Fast Nearest Neighbor Searc...

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Asilomar conference on signals, Systems & Computers

作者： Hye-Yeon Cheong Antonio Ortega Signal and Image Processing Institute University of Southern California Los Angeles CA USA

The problem of given a query vector finding its nearest neighbor within a large set of vectors in high dimensional space arises in many applications. It often poses serious computational challenges due to the size of data point set (database), dimensionality of the search space, and the metric complexity. There exists a wealth of results in the literature that reduce complexity primarily based on altering the data set while still computing the chosen distance metric to full precision. However further significant simplification is attainable with our proposed approach which reduces the search metric computation resolution by applying non-uniform quantization within the metric computation process, in such a way that the minimum distance ranking is most likely to be preserved. This paper provides analytical and experimental studies of our proposed approach. We present an analytical formulation of the search performance measure that gives insight into understanding this approach. Based on this formulation we present a quantizer optimized to minimize the impact of quantization on identifying the nearest neighbor. The main advantages of this approach are that: i) it can reduce the number and complexity of required arithmetic operations significantly, ii) complexity does not increase with the order of l p norm or input bit size, and increases only slowly with dimensionality, and most importantly iii) the penalty to be paid in performance for the complexity reduction is very small if designed optimally. Motion estimation and compensation for video coding is chosen as an example application. Without requiring any filtering, transform, or sorting process, using a simple hardware oriented mapping, our experimental results show on average 0.05 dB loss using only 1 bit per pixel distance (0.01 dB when 2 bits are used) instead of typical 8 or 16 bits metrics.

关键词： Quantization Nearest neighbor searches Computer applications Motion estimation Databases Performance analysis Arithmetic Video coding Filtering Sorting

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Extraction of PD data from UWB measurements on motor stator bars fed by an IGBT inverter

Extraction of PD data from UWB measurements on motor stator ...

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conference on Electrical Insulation and Dielectric Phenomena, (CEIDP)

作者： L. Angrisani M. Di Lorenzo del Casale M. D'Arco C. Petrarca Dip. di Ing. Elettrica Università di Napoli Napoli Italy Dip. di Ing. Inf. e lng. Elettr. Università di Salerno Fisciano Italy Dip. di Ing. Elettrica Università di Napoli Federico II Napoli Italy

The modem power converters adopted for adjustable speed drive applications are based on switching devices, such as IGBTs, characterised by very fast commutations and high switching frequencies. With such low switching times (fractions of /spl mu/s), problems have become apparent on the long-term behaviour of the motor insulation. Indeed, the inverter output voltage is not pure sinusoidal but it presents sharp pulses in correspondence with the power devices commutations and it is characterised by a considerable harmonic content. Due to supplementary stresses caused by commutations and to space charge formation inside the insulation, the dielectric strength of the materials decreases as a result of the more intense partial discharge (PD) activity and the life expectancy of the machine is sensibly reduced. Since little is known on the PD behaviour of the insulating material under such distorted voltages, an experimental activity has been carried out by performing Ultra-Wide Band detection of partial discharges on specimen subjected to typical inverter output voltages. The analysis of the detected signals has been carried out by means of a suitable digital signal processing approach, based on the wavelet Transform, capable of extracting the PD pulses occurring during the overvoltages caused by the commutations of semiconducting devices.

关键词： Data mining Stator bars Insulated gate bipolar transistors Inverters Partial discharges Commutation Dielectrics and electrical insulation Voltage Dielectric materials Modems

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Digital watermarking scheme for image authentication

Digital watermarking scheme for image authentication

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International conference on Communication and signal processing

作者： Lakshmi Priya, C. V. Nelwin Raj, N. R. SreeChitraThirunal College of Engineering Thiruvananthapuram India

Digital image watermarking process is definite as to insert information of digital into digital signal. This is an efficient solution to avoid illegal copying of information from multimedia networks. Many watermarking algorithms have been developed and each of them has its own individuality because of its variety of applications. A new algorithm able to solve most of the practical issues of watermarking is designed. Watermarking alone is not sufficient to prevent the unauthorized manipulations of data unless a proper protection protocol is established. An efficient watermarking algorithm should satisfy an optimal trade-off between three factors such the capacity, robustness and imperceptibility. The proposed algorithm uses the advantage of singular value decomposition (SVD), discrete wavelet transform (DWT) and homomorphic filtering. Finally, the efficiency of the result is evaluated using various quality measurements and the watermarked image is encrypted to increase the security level.

关键词： Digital water marking DWT SVD Homomorphic filtering Encryption

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image deconvolution and PSF reconstruction with STARRED: a wavelet-based two-channel method optimized for light-curve extraction

arXiv

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arXiv 2024年

作者： Millon, Martin Michalewicz, Kevin Dux, Frédéric Courbin, Frédéric Marshall, Philip J. Kavli Institute for Particle Astrophysics and Cosmology Department of Physics Stanford University StanfordCA94305 United States Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom European Southern Observatory Alonso de Córdova 3107 Vitacura Santiago Chile Observatoire de Sauverny Versoix1290 Switzerland SLAC National Accelerator Laboratory Menlo ParkCA94025 United States

We present starred, a Point Spread Function (PSF) reconstruction, two-channel deconvolution, and light curve extraction method designed for high-precision photometric measurements in imaging time series. An improved resolution of the data is targeted rather than an infinite one, thereby minimizing deconvolution artifacts. In addition, starred performs a joint deconvolution of all available data, accounting for epoch-to-epoch variations of the PSF and decomposing the resulting deconvolved image into a point source and an extended source channel. The output is a high signal-to-noise, high resolution frame combining all data, and the photometry of all point sources in the field of view as a function of time. Of note, starred also provides exquisite PSF models for each data frame. We showcase three applications of starred in the context of the imminent LSST survey and of JWST imaging: i) the extraction of supernovae light curves and the scene representation of their host galaxy, ii) the extraction of lensed quasar light curves for time-delay cosmography, and iii) the measurement of the spectral energy distribution of globular clusters in the "Sparkler", a galaxy at redshift z=1.378 strongly lensed by the galaxy cluster SMACS J0723.3-7327. starred is implemented in jax, leveraging automatic differentiation and GPU acceleration. This enables rapid processing of large time-domain datasets, positioning the method as a powerful tool for extracting light curves from the multitude of lensed or unlensed variable and transient objects in the Rubin-LSST data, even when blended with intervening objects. Copyright © 2024, The Authors. All rights reserved.

关键词： Supernovae

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