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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems IV"

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algorithms and Fundamental Limits for Unlabeled Detection Using Types

Algorithms and Fundamental Limits for Unlabeled Detection Us...

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作者： Marano, Stefano Willett, Peter K. Dipartimento di Ingegneria dell'Informazione Ed Elettricae Matematica Applicata University of Salerno FiscianoI-84084 Italy Department of Electrical and Computer Engineering University of Connecticut StorrsCT06269-2157 United States

We deal with the classical problem of testing two simple statistical hypotheses but, as a new element, it is assumed that the data vector is observed after an unknown permutation of its entries. What is the fundamental limit for the detection performance in this case? How much information for detection is contained in the entry values and how much in their positions? In the first part of this paper, we answer these questions. In the second part, we focus on practical algorithms. A low-complexity detector solves the detection problem without attempting to estimate the permutation. A modified version of the auction algorithm is then considered, and two greedy algorithms with affordable worst case complexity are presented. The detection operational characteristics of these detectors are investigated by computer experiments. The problem we address is referred to as unlabeled detection and is motivated by large sensor network applications, but applications are also foreseen in different fields, including image processing, social sensing, genome research, and molecular communication. © 1991-2012 IEEE.

关键词： image processing

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Automated change feature extraction systems in remote sensing

Automated change feature extraction systems in remote sensin...

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conference on Applications of Digital image processing XXI

作者： Dai, XL N Carolina State Univ Ctr Earth Observ Raleigh NC 27695 USA

ISBN: (纸本)0819429155

To enhance the ability of remote sensing system to provide accurate, timely, and complete geospatial information at regional and/or global scale, an automated change detection system has been and will continue to be one of the important yet challenging problems in remote sensing. This research was designed to evaluate the requirements and develop the techniques for an automated change detection system at landscape level using various geospatial data including multisensor remotely sensed imagery and ancillary data layers. These techniques are included in three subsystems: automated computer image understanding, multisource data fusion, and database updating and visualization. This paper summarizes what has been achieved so far in this research. The experiments have been focusing on three major interrelated components. In the first component, the impact of misregistration on the accuracy of remotely sensed land cover change detection was quantitatively investigated using Landsat Thematic Mapper (TM) images. In the second component, a new feature-based approach to automated multitemporal and multisensor image registration was developed. Feature matching was done in both feature space and image space based on moment invariant distance and chain code correlation. The characteristic of this technique is that it combines moment invariant shape descriptors with chain code correlation to establish the correspondences between regions in two images. In the third component, the algorithms for an automated change detection system utilizing neural networks were developed and implemented. This work has implications on improving the efficiency and accuracy of the change feature extraction and quantification at all levels of applications ranging from local to global in scale.

关键词： change detection satellite image processing automated remote sensing image registration neural networks feature-based

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Stopping rules for active contour segmentation of ultrasound cardiac images

Stopping rules for active contour segmentation of ultrasound...

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Medical Imaging 2005 conference

作者： Tao, Z Tagare, HD Yale Univ Dept Elect Engn New Haven CT 06520 USA

ISBN: (纸本)0819457213

The presence of speckle (a spatial stochastic process in an ultrasound image) makes ultrasound segmentation difficult. Speckle introduces local minima in the MAP energy function of an active contour, and when evolving under gradient descent, the contour gets trapped in a spurious local minimum. In this paper, we propose an alternate technique for evolving a MAP active contour. The technique has two parts: a deterministic evolution strategy called tunneling descent which escapes from spurious local minima, and a stopping rule for terminating the evolution. The combination gives an algorithm that is robust and gives good segmentations. The algorithm also benefits from having only a few free parameters which do not require tweaking. We present the conceptual framework of the algorithm in this paper, and study the impact of different stopping rules on the performance of the algorithm. The algorithm is used to segment the endocardium in cardiac ultrasound images. We present segmentation results in this paper and an experimental evaluation of different stopping rules on the performance of the algorithm. Although the algorithm is presented as an ultrasound segmentation technique, in fact, it can be used to segment any first-order texture boundary.

关键词： image segmentation Ultrasonography Blood Speckle Tissues Echocardiography image processing algorithms and systems Algorithm development Error analysis Stochastic processes

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An insight into the estimation of MIMO propagation parameters using the sage algorithm

An insight into the estimation of MIMO propagation parameter...

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2nd European conference on Antennas and Propagation, EuCAP 2007

作者： Matthaiou, M. Razavi-Ghods, N. Laurenson, D.I. Salous, S. Institute for Digital Communications Joint Research Institute for Signal and Image Processing University of Edinburgh United Kingdom Cavendish Laboratory University of Cambridge Cambridge United Kingdom Centre for Communication Systems University of Durham Durham United Kingdom

ISBN: (纸本)9780863418426

In this contribution, we provide a thorough review of the application of SAGE (space-alternating generalised expectation-maximisation) algorithm to the problem of parameter estimation for MIMO (multiple-input multiple-output) systems. It is well established that the SAGE algorithms yields a superior performance compared to other estimation algorithms in terms of accuracy and robustness. For our investigation, we consider both the time and frequency domain evaluations of the algorithm since each domain requires a different signal model.

关键词： Frequency domain analysis

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Analysis of the Effects of image Transformation, Template Selection, and Partial Information on Face Recognition with Time-Varying Expressions For Homeland Security Applications

Analysis of the Effects of Image Transformation, Template Se...

引用

13th IEEE International conference on Technologies for Homeland Security (HST)

作者： Voynichka, Iliana V. Megherbi, Dalila B. Univ Massachusetts Dept Elect & Comp Engn CMINDS Res Ctr Lowell MA 01854 USA

ISBN: (纸本)9781479915354;9781479939633

Facial recognition, especially with time-varying facial expressions and/or disguises, is crucial in many homeland security applications. The recent Boston Marathon attack is one example reminder of the importance of developing accurate and reliable facial recognition algorithms. While various face recognition algorithms have been proposed in the literature, unfortunately many of them still remain in their infancy. This is mainly due to their lack of high recognition rates in the presence of varying image face artifacts and conditions. In order to develop more accurate facial recognition systems there is a primary need to identify and, as much as possible, derive some of the causes that may affect some face recognition accuracy rates. The main contribution of this paper is the investigation and analysis of how and what factors, other than illumination noise, and occlusion, may affect the recognition accuracy rate of some of the most popular and currently widely used face recognition algorithms, namely, Eigenface-based, Fisher-facebased and Direct Correlation-based ones. In particular, in this work we show the effects, on these facial recognition accuracy, of facial reasonable registration with or without off-the-plane face rotation, the type and number of individual's face template(s) selection, and the type and increasing amount of partial facial information contained in face images. Finally experimental results are presented to demonstrate the potential value and importance of each of these proposed factors on facial recognition.

关键词： component Machine Learning Computer and Machine Vision Computational Intelligence Digital image processing Facial Recognition Biometrics eigenfaces fisher-faces correlation-based face recognition

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Local Gabor Wavelet-Based Feature Extraction and Evaluation 3rd

Local Gabor Wavelet-Based Feature Extraction and Evaluation

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3rd International conference on Advanced Computing, Networking, and Informatics (ICACNI)

作者： Malathi, T. Bhuyan, M. K. Indian Inst Technol Dept Elect & Elect Engn Gauhati 781039 India

ISBN: (纸本)9788132225386;9788132225379

Feature extraction is an essential step in many image processing and computer vision applications. It is quite desirable that the extracted features can effectively represent an image. Furthermore, the dominant information visually perceived by human beings should be efficiently represented by the extracted features. Over the last few decades, different algorithms are proposed to address the major issues of image representations by the efficient features. Gabor wavelet is one of the most widely used filters for image feature extraction. Existing Gabor wavelet-based feature extraction methodologies unnecessarily use both the real and the imaginary coefficients, which are subsequently processed by dimensionality reduction techniques such as PCA, LDA etc. This procedure ultimately affects the overall performance of the algorithm in terms of memory requirement and the computational complexity. To address this particular issue, we proposed a local image feature extraction method by using a Gabor wavelet. In our method, an image is divided into overlapping image blocks, and subsequently each of the image blocks are separately filtered out by Gabor wavelet. Finally, the extracted coefficients are concatenated to get the proposed local feature vector. The efficacy and effectiveness of the proposed feature extraction method is evaluated using the estimation of mean square error (MSE), peak signal-to-noise ratio (PSNR), and the correlation coefficient (CC) by reconstructing the original image using the extracted features, and compared it with the original input image. All these performance evaluation measures clearly show that real coefficients of the Gabor filter alone can effectively represent an image as compared to the methods which utilize either the imaginary coefficients or the both. The major novelty of our method lies on our claim-capability of the real coefficients of a Gabor filter for image representation.

关键词： image feature extraction Gabor filter image reconstruction

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Fairness-aware Dimensionality Reduction 31

Fairness-aware Dimensionality Reduction

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31st European Signal processing conference, EUSIPCO 2023

作者： Kose, O. Deniz Shen, Yanning Electrical Engineering and Computer Science University of California Irvine Irvine United States

ISBN: (纸本)9789464593600

In this era of digitalization, the massive increase in available data leads to great potential for advancing various domains. However, the available data, such as images, videos, and speech signals, generally lie in high-dimensional space, which calls for efficient dimensionality reduction techniques to process them efficiently. Furthermore, while the fairness of algorithms is essential for their deployment in real-world systems, the effect of dimensionality reduction on fairness is an under-explored research area. Motivated by this, this paper puts forth a fairness-aware dimensionality reduction framework that is capable of properly compressing the data while mitigating bias. Specifically, our design targets at reducing the correlation between the compressed data and sensitive attributes, while projecting the data into a new coordinate system where most of its variation can be described. Experimental results on the CelebA dataset demonstrate that the proposed dimensionality reduction framework can improve group fairness measures for image classification while providing comparable utility to the conventional techniques. © 2023 European Signal processing conference, EUSIPCO. All rights reserved.

关键词： image classification

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Implementation of different image edge detection algorithms on a real embedded ADAS platform

Implementation of different image edge detection algorithms ...

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2021 Zooming Innovation in Consumer Technologies conference, ZINC 2021

作者： Coric, Dario Kastelan, ivan Herceg, Marijan Pjevalica, Nebojsa Institute RT-RK Osijek Llc for Information Technology Osijek Croatia RT-RK Institute for Computer Based Systems Novi Sad21000 Serbia Computer Science and Information Technology Osijek Faculty of Electrical Engineering Osijek Croatia University of Novi Sad Faculty of Technical Sciences Novi Sad Serbia

ISBN: (纸本)9781665404174

Advanced Driver-Assistance systems (ADASs) are becoming more and more popular in modern vehicles in the last years. A number of them are based on processing the images captured by in-vehicle cameras. Furthermore, in image processing-based ADAS algorithms one of the most important steps often is edge detection. Therefore, it is important to properly choose the edge detection method, to achieve high performance and low processing time. Due to limited hardware resources available when using real ADAS platforms, the trade-off is needed. In this paper, the implementation of four different edge detection operators (Sobel, Prewitt, Laplace and Canny) onto a real ADAS Alpha board is performed. The implementation is performed using the Vision Software Development Kit (SDK), which is a multi-processor software platform specifically optimized to work with Texas Instruments (TI) systems-On-Chip (SoCs) that Alpha board consists of. To test the operators' performance in a real ADAS operational environment, the Berkeley dataset is used. The output results of each edge detector are compared to available ground truth labeled images from the Berkeley dataset to check which detector achieves the highest performance in terms of edge detection accuracy. Furthermore, the operators are compared in terms of execution time and memory usage. It was shown that Canny operator requires the longest execution time and the highest amount of memory, but it also achieves the highest edge detection accuracy. It is also shown that the trade-off between detector accuracy and its requirements can be achieved in certain situations where it is acceptable. © 2021 IEEE.

关键词： Advanced driver assistance systems

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An occlusion robust likelihood integration method for multi-camera people head tracking

An occlusion robust likelihood integration method for multi-...

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conference on Intelligent Robots and Computer Vision XXV - algorithms, Techniques, and Active Vision

作者： Matsumoto, Yusuke Kato, Takekazu Wada, Toshikazu Wakayama Univ Grad Sch Syst Engn Wakayama 6408510 Japan

ISBN: (纸本)9780819469243

This paper presents a novel method for human head tracking using multiple cameras. Most existing methods estimate 3D target position according to 2D tracking results at different viewpoints. This framework can be easily affected by the inconsistent tracking results on 2D images, which leads 3D tracking failure. For solving this problem, an extension of CONDENSATION Using multiple images has been proposed. The method generates many hypotheses on a target (human head) in 3D space and estimates the likelihood of each hypothesis by integrating viewpoint dependent likelihood values of 2D hypotheses projected onto image planes. In theory, viewpoint dependent likelihood values should be integrated by multiplication, however, it is easily affected by occlusions. Thus we investigate this problem and propose a novel likelihood integration method in this paper and implemented a prototype system consisting of six sets of a PC and a camera. We confirmed the robustness against occlusions.

关键词： Head Cameras 3D image processing 3D acquisition Detection and tracking algorithms Prototyping 3D modeling Automatic tracking Imaging systems Lead

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Recognition of Lawn Weeds based on Retinex Algorithm with Local Density Fusion 15

Recognition of Lawn Weeds based on Retinex Algorithm with Lo...

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15th International conference on Signal processing systems, ICSPS 2023

作者： Hua, Chunjian Li, Xiuqin Zhang, Airong School of Mechanical Engineering Jiangnan University Jiangsu China Wuxi Pioneer Intelligent Equipment Company China

ISBN: (纸本)9781510675056

In order to solve the problem of difficulty in segmenting the foreground of lawn weed images due to the similarity between the foreground and background grayscale, this paper proposes a Retinex enhancement algorithm based on local density fusion. Firstly, image preprocessing is completed based on local variance to realize prominent image foreground and smooth cluttered background;Secondly, using multi threshold segmentation and operational differentiation, pixels are divided into three categories: foreground, background, and pixels to be subdivided. Local density is used to extract spatial information of pixels to be subdivided;Finally, the sigmoid function is used to optimize the reflection component grayscale transformation coefficient, achieving the fusion of local density information and obtaining the final image. The results show that the algorithm proposed in this paper expands the gray difference between weeds and lawn grass while suppressing background noise;Compared with other enhancement algorithms, the peak signal-to-noise ratio, average running time, and segmentation accuracy have all been improved greatly. At the same time, through image analysis, it has been found that the algorithm results in occasional problems of uneven brightness and over segmentation of fine leaf weeds in the image. In response to these two problems, this article finally proposes two corresponding optimization measures, namely global brightness adjustment based on a new adaptive gamma function and Retinex reflection component saturation adjustment based on AHE. © 2024 SPIE.

关键词： image enhancement

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