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3rd International symposium on image and signal processing and Analysis (ISPA)

作者： Cvejic, N Seppänen, T Univ Oulu Informat Proc Lab MediaTeam Oulu Grp FIN-90014 Oulu Finland

ISBN: (纸本)953184061X

In this work, we present a novel robust audio watermarking method in wavelet domain. Embedding Of watermarks is performed in a perceptually significant set of sub-bands of the host audio. In order to enhance security, watermark is embedded in a randomly selected sub-band of the host audio according to a secret key. Watermark embedding to a mapped subband is done in a predefined time period, similarly to frequency hopping approach in digital communications. Detection method is a statistical method motivated by modified patchwork algorithm, relying on large data sets. Using simple Haar decomposition and test statistics, the algorithm proved itself in the terms of computational complexity. Subjective listening test proved high perceptual transparency of the watermarked audio clips. Using embedding rate of 4.61 bps, high robustness against common audio watermarking attacks was obtained, with average bit error rate lower than 1%.

关键词： Bit error rate computational complexity Digital communication Robustness Security Spread spectrum communication Statistical analysis Testing Watermarking Wavelet domain

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Artificial intelligence and image processing approaches in damage assessment and material evaluation

Artificial intelligence and image processing approaches in d...

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International Conference on computational intelligence for Modelling, Control and Automation/International Conference on Intelligent Agents Web Technologies and International Commerce

作者： Kumar, S. S. Taheri, F. Islam, M. R. Dalhousie Univ Dept Civil Engn Halifax NS B3J 1Z1 Canada

ISBN: (纸本)0769525040

The Ultrasonic is an inspection technique (UT), which employs high frequency acoustic waves to probe the sample being inspected. As the acoustic wave penetrates the sample, the wave is attenuated and/or reflected as a result of variation in the density (sound velocity) of the material. By observing and post processing the returned signal, be it the reflected signal or the signal emanating from the opposite side of the sample, one can effectively evaluate the material's characteristics such as material microstructures, as well as flaws existing in the material. This paper describes different Artificial intelligence (AI) and image processing methods, which could be utilized to investigate various defects in metals as well as composites. The proposed system is highly robust and effective in situations where a large number of similar samples are to be investigated. The proposed methods utilizes Artificial Neural Networks (ANN), Fuzzy Logic and image Analysis to recognize various types of defects in a given specimen. image processing and wavelets techniques are used to determine the details of the damage geometry. The above system is an integral part of a robust damage analysis software under the development. An Adaptive Neuro Fuzzy Inference System is also being developed for composites, suggestive repair mechanicsm. MATLAB language is used in developing a real time automated damage assessment and evaluation prototype system.

关键词： Artificial intelligence

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A simulator of synthetic aperture radar images;land, ocean surface, and man-made targets

A simulator of synthetic aperture radar images;land, ocean s...

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ieee International Geoscience and Remote Sensing symposium

作者： Tsuchida, M Suwa, K Iwamoto, M Mitsubishi Electr Corp Informat Technol R&D Ctr Kamakura Kanagawa 2478501 Japan

ISBN: (纸本)0780387422

Synthetic aperture radar (SAR) images are very useful for many applications. However, SAR images require a great deal of experience for the interpretation, since the appearances are very different from optical images. Additionally, the appearances change significantly by the observational condition, such as frequency and incident angle. We propose a SAR image simulating algorithin developed for the aid of the SAR image analysis and training. The simulator is also intended to support the SAR system configuration design by providing the expected images. The main features of the algorithm) are the capability of wide area simulation and the low computational costs. The simulated image of 10 km square area is shown and compared with the real image.

关键词： terrain mapping radar imaging geophysical signal processing remote sensing by radar synthetic aperture radar oceanographic techniques target tracking radar tracking synthetic aperture radar images SAR image simulating algorithm man-made targets ocean surface targets land targets optical images SAR image analysis SAR training SAR system configuration design wide area simulation computational costs Synthetic aperture radar Radar polarimetry Radar remote sensing radar target tracking Optical Imaging Marine technology geophysical signal processing terrain mapping Radar imaging image analysis Target tracking ocean surface

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image Regularization with Morphological Gradient Priors Using Optimal Structuring Elements for Each Pixel

Image Regularization with Morphological Gradient Priors Usin...

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International symposium on Intelligent signal processing and Communication Systems (lSPACS)

作者： Oohara, Shoya Oka, Hirotaka Muneyasu, Mitsuji Yoshida, Soh Nakashizuka, Makoto Kansai Univ Fac Engn Sci 3-3-35 Yamate Cho Suita Osaka 5648680 Japan Chiba Inst Technol Fac Engn 2-17-1 Tsudanuma Narashino Chiba 2750016 Japan

ISBN: (纸本)9781728130385

As an image prior for image restoration, the use of the sum of the morphological gradient for an image has been proposed. In this paper, we propose a method of optimizing the structuring element (SE) for each pixel, in particular, by greatly reducing the computational burden for optimization by adopting a new evaluation method for the SE in simulated annealing. By optimizing the SE for each pixel, edges of the image can be faithfully evaluated, and the improvement of restoration accuracy can be expected. An experimental result shows the effectiveness of the proposed method.

关键词： morphology morphological gradient total variation regularization image restoration simulated annealing

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Object Detection in Satellite images Based on Active Learning Utilizing Visual Explanation 11

Object Detection in Satellite Images Based on Active Learnin...

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11th International symposium on image and signal processing and Analysis (ISPA)

作者： Uehara, Kazuki Nosato, Hirokazu Murakawa, Masahiro Sakanashi, Hidenori Natl Inst Adv Ind Sci & Technol Artificial Intelligence Res Ctr AIRC Tsukuba Ibaraki Japan

ISBN: (纸本)9781728131405

Convolutional neural networks (CNNs) have attracted much attention for object detection in satellite images. However, creating an annotated dataset requires a lot of time and user workload due to which the remote sensing domain has insufficient labeled datasets for training CNNs. We exploit an active learning (AL) framework for training CNNs with a small labeled dataset. AL obtains the training dataset by asking a human user to label the samples. For efficient AL, an intelligent query strategy is essential because the performance of a CNN depends on the collected dataset. Thus, in this study, we propose a query strategy to train CNNs effectively;this is done by choosing effective samples for training both the classifier and feature extractor. The strategy selects samples according to the gap between the classifier's prediction and visual explanation, which is the class discriminative part of an image derived from the extracted feature maps. Experimental result shows that a CNN trained with samples queried by our strategy had a 95% reduction in training samples requirement while maintaining 94% detection performance compared to a CNN trained with a complete dataset. Furthermore, the proposed strategy also reduced the required training samples by 30% compared to the conventional strategy to yield the same performance.

关键词： Active learning Visual explanation Annotation Object detection Satellite images

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Magnetic Properties-Based Range image Descriptor 15

Magnetic Properties-Based Range Image Descriptor

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15th International symposium on computational intelligence and Design, ISCID 2022

作者： Li, Taifeng Chen, Bo Zhang, Feifei Lin, Kun Dong, Qiang Purification Equipment Research Institute of CSIC Handan China

ISBN: (纸本)9781665456166

With the development of a new generation of information technology, range images are being used more and more in the fields of image processing, computer vision, and pattern recognition. More concretely, range images play an increasingly important role in autopilot, medical analysis, and quality inspection. As we all know, the range image is composed of a series of three-dimensional (3D) scattered points. Due to limitations of coordinate data, it makes extremely difficult to distinguish the difference between adjacent points. This paper is such an attempt to address this issue. Through the similarity analysis of electron cloud and range image, this paper presents a range image descriptor based on magnetic properties. Benefit from the classical theory of particle motion in magnetic field, Lorentz force, rotation radius, rotation period, and volume ratio parameters are calculated for each point. On that basis, a complete range image descriptor is designed to encode the potential connection of each point from a higher dimension. Experimental results show the discriminating power of the proposed method. Focusing on range image description, the simple structure of our algorithm can effectively improve the efficiency and accuracy of image processing. © 2022 ieee.

关键词： Magnetic properties

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Humanistic computing: "WearComp" as a new framework and application for intelligent signal processing

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PROCEEDINGS OF THE ieee 1998年第11期86卷 2123-2151页

作者： Mann, S Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

Humanistic computing is proposed as a new signal processing framework in which the processing apparatus is inextricably intertwined with the natural capabilities of our human body and mind. Rather than trying to emulate human intelligence, humanistic computing recognizes that the human brain is perhaps the best neural network of ifs kind, and that there are many new signal processing applications (within the domain of personal technologies) that can make use of this excellent but often overlooked processor. The emphasis of this paper is on personal imaging applications of humanistic computing, to take a first step toward an intelligent wearable camera system that can allow us to effortlessly capture our day-to-day experiences, help us remember and see better, provide us with personal safety through crime reduction, and facilitate new forms of communication through collective connected humanistic computing. The author's wearable signal processing hardware, which began as a cumbersome backpack-based photographic apparatus of the 1970's and evolved into a clothing-based apparatus in the early 1980's, currently provides the computational power of a UNIX workstation concealed within ordinary-looking eyeglasses and clothing. Thus it may be worn continuously during all facets of ordinary day-to-day living, so that, through long-term adaptation, it begins to function as a true extension of the mind and body.

关键词： consumer electronics cybernetic sciences human factors humanistic property protection image processing machine vision mobile communication photoquantigraphic imaging signals

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Development of A Classification Architecture for images Represented Using Quantum Theory : ∗using IBM QISKIT Liberaries 3

Development of A Classification Architecture for Images Repr...

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3rd International Conference on Artificial intelligence and signal processing, AISP 2023

作者： Singh, Barkha Indu, S. Majumdar, Sudipta Delhi Technological University Department of Electronics and Communication Engineering Shah-bad Daulatpur Main Bawana Road Delhi110042 India Delhi Technological University Department of Electronics and Communication Engineering Delhi110042 India

ISBN: (纸本)9798350320749

Quantum image processing is paramount in image processing-based research areas nowadays due to the less computational time. This paper presents the quantum mechanic-based image denoising model. Also, This article discusses the quantum boolean mean filter and new quantum-boolean image denoising that are connected to computational basis states. This paper describes basic quantum information processing principles, new and better image representation approaches, quantum image processing implementation problems, quantum boolean mean filtering approach for image denoising observation using appropriate matrice, and finally, a work proposal for future work and conclusion. A comparison table of different classification techniques is also included in the paper. © 2023 ieee.

关键词： image denoising

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Comparative study of band-power extraction techniques for Motor imagery classification

Comparative study of band-power extraction techniques for Mo...

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ieee symposium on computational intelligence, Cognitive Algorithms, Mind, and Brain

作者： Brodu, Nicolas Lotte, Fabien Lécuyer, Anatole Bât 22 Campus de Beaulieu University of Rennes 1 35042 Rennes Cedex France Signal Processing Department Brain-Computer Interface Laboratory 1 Fusionopolis way 138632 Singapore Singapore INRIA Campus de Beaulieu Avenue du Général Leclerc 35042 Rennes Cedex France

ISBN: (纸本)9781424498918

We review different techniques for extracting the power information contained in frequency bands in the context of electroencephalography (EEG) based Brain-Computer Interfaces (BCI). In this domain it is common to apply only one algorithm for extracting the power information. However previous work and our current study confirm that one may indeed expect varying degrees of success by choosing inadequate algorithms for the power extraction. Our results suggest that on average one algorithm seems superior for extracting the power information for Motor imagery tasks : the application of a Morlet wavelet on the raw EEG signals, with the time-frequency resolution tradeoff selected by cross-validation. © 2011 ieee.

关键词： Electroencephalography

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SCALE-SPACE FOR DISCRETE signalS

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ieee TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE intelligence 1990年第3期12卷 234-254页

作者： LINDEBERG, T Comput. Vision & Associative Pattern Process. Lab. R. Inst. of Technol. Stockholm Sweden

A basic and extensive treatment of discrete aspects of the scale-space theory is presented. A genuinely discrete scale-space theory is developed and its connection to the continuous scale-space theory is explained. Special attention is given to discretization effects, which occur when results from the continuous scale-space theory are to be implemented computationally. The 1D problem is solved completely in an axiomatic manner. For the 2D problem, the author discusses how the 2D discrete scale space should be constructed. The main results are as follows: the proper way to apply the scale-space theory to discrete signals and discrete images is by discretization of the diffusion equation, not the convolution integral; the discrete scale space obtained in this way can be described by convolution with the kernel, which is the discrete analog of the Gaussian kernel, a scale-space implementation based on the sampled Gaussian kernel might lead to undesirable effects and computational problems, especially at fine levels of scale; the 1D discrete smoothing transformations can be characterized exactly and a complete catalogue is given; all finite support 1D discrete smoothing transformations arise from repeated averaging over two adjacent elements (the limit case of such an averaging process is described); and the symmetric 1D discrete smoothing kernels are nonnegative and unimodal, in both the spatial and the frequency domain.

关键词： signal resolution Kernel Smoothing methods Convolution image resolution Laplace equations Filtering signal processing Computer vision INSPEC: Controlled Indexing signal processing discrete systems INSPEC: Non-Controlled Indexing frequency domain signal processing nonnegative kernels unimodal kernels spatial domain discrete signals discrete scale-space theory diffusion equation Gaussian kernel discrete smoothing transformations

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