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

共 12673 条记录，以下是4541-4550 订阅

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Design of Simulation Platform for Missile-borne SAR Imaging 8

Design of Simulation Platform for Missile-borne SAR Imaging

引用

8th International conference on Intelligent Human-Machine systems and Cybernetics (IHMSC)

作者： Chen, Qi Zhu, Mingbo Li, Xiangping Guo, Tao Zou, Xiaohai Naval Aeronaut & Astronaut Univ Dept Elect & Informat Engn Yantai Peoples R China CEMEE State Key Lab Luoyang Peoples R China

ISBN: (纸本)9781509007684

Missile-borne synthetic aperture radar (SAR) imaging system is built up according to actual working principle, it uses the input data and embedded algorithms to simulate echo, then generate SAR image. Relevant algorithms is analyzed, a SAR echo simulation method based on graphic processing unit (GPU) acceleration is presented to satisfy the request of real-time. Simulation platform realized by MATLAB GUI turns out to be reliable and interactive, it can meet the demand for missile-borne SAR system test and development, and has some practical value.

关键词： Synthetic aperture radar (SAR) Graphic processing unit (GPU) Simulation platform Interactive

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Target Detection in Hyperspectral images 24

Target Detection in Hyperspectral Images

引用

24th Signal processing and Communication Application conference (SIU)

作者： Karakaya, Ahmet Yuksel, Seniha Esen Aselsan Ankara Turkey Hacettepe Univ Elekt & Elekt Muhendisligi Bolumu Ankara Turkey

ISBN: (纸本)9781509016792

Target detection in hyperspectral images is important in many applications including search and rescue operations, defense systems, mineral exploration, mine detection and border security. In this study, the goal is to detect the nine sub-pixel targets, from seven different materials, that are placed around the town. For this purpose, eight hyperspectral target detection algorithms are compared and the three most successful algorithms are fused together. The results are compared with ROC curves, and it is found that the fusion of signed ACE, CEM and AMSD algorithms can achieve very successfull results in comparison to the other algorithms.

关键词： hyperspectral image target detection

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Zero Resource Anti-Spoofing Detection for Unit Selection Based Synthetic Speech using image Spectrogram Artifacts

Zero Resource Anti-Spoofing Detection for Unit Selection Bas...

引用

Asia-Pacific Signal and Information processing Association Annual Summit and conference (APSIPA)

作者： Leow, Su Jun Chng, Eng Siong Lee, Chin-hui Nanyang Technol Univ Singapore Singapore Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9789881476821

Synthesized speech poses a serious threat to speaker verification systems, which is aggravated by speech synthesis systems becoming more freely available and easily adaptable to a target speaker. This motivated research into synthetic speech detection to circumvent the threat. Although current algorithms are effective in the detection of HMM-based speech synthesizers, unit selection based speech synthesizers remain a serious threat due to its ability to generate spoofing speech which easily overcame existing detectors. Current error rates for their detection is a lot higher than that obtained for other spoofing methods. This paper proposes a detection algorithm to counter unit selection based synthesis speech. It is free of training and exploits presence of artifacts in image spectrogram to perform detection. To the best of our knowledge, this is the first attempt targeted for unit selection based synthesis speech. Experimental results show the effectiveness of the proposed approach.

关键词： Speech synthesis

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Road Sign Recognition System on Raspberry Pi

Road Sign Recognition System on Raspberry Pi

引用

IEEE Long Island systems, Applications and Technology conference (LISAT)

作者： Bilgin, Enis Robila, Stefan Montclair State Univ Dept Comp Sci Montclair NJ 07043 USA

ISBN: (纸本)9781467384902

Digital image processing, i.e. the use of computer systems to process pictures, has applications in many fields, including of medicine, space exploration, geology and oceanography and continues to increase in its applicability. The main objective of this paper is to demonstrate the ability of image processing algorithms on a small computing platform. Specifically we created a road sign recognition system based on an embedded system that reads and recognizes speed signs. The paper describes the characteristics of speed signs, requirements and difficulties behind implementing a real-time base system with embedded system, and how to deal with numbers using image processing techniques based on shape and dimension analysis. The paper also shows the techniques used for classification and recognition. Color analysis also plays a specifically important role in many other different applications for road sign detection, this paper points to many problems regarding stability of color detection due to daylight conditions, so absence of color model can led a better solution. In this project lightweight techniques were mainly used due to limitation of real-time based application and Raspberry Pi capabilities. Raspberry Pi is the main target for the implementation, as it provides an interface between sensors, database, and image processing results, while also performing functions to manipulate peripheral units (usb dongle, keyboard etc.).

关键词： component Digital image processing Raspberry Pi Embedded System Road Sign Recognition

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Identifying and classifying cancerous cells based on the Ki67 detector 2

Identifying and classifying cancerous cells based on the Ki6...

引用

2nd International conference on image processing, Applications and systems (IPAS)

作者： Seddik, Hassen Saidani, Bechir Univ Tunis ENSIT Tunis Tunisia

ISBN: (纸本)9781509016457

The image processing arose from the idea of the necessity to replace the human observer by a machine. The interest of this paper is to replace the medical image by information interpretable. Usually, experts have manually performed to count the cell nuclei biopsy samples, one by one. This method ensures that accuracy is achieved in the final diagnosis delivered by pathologists, but the time until the patient is notified can vary from weeks to months depending on the laboratory resources. Cancer developing speed is also a limiting factor, so the sooner the disease is discovered the better and quicker the patient can start with the treatment or preparations for surgery can be arranged. Promptness in cancer recognition increases the chances to overcome this illness that affects every year more and more men as the world population's life expectancy increases. So, for this reason, it has proposed an automatic method. To return the more reliable and fast diagnosis, we applied a method based on tools and algorithms. The chain of this processing is begun with the segmentation to separate the various constituent zones the image. Secondly, we have the step of detecting the edges of the prostatic cells as well their center. Finally, we have the step of counting where we are going to find a score for the diagnosis.

关键词： image processing segmentation detection of cells cancer counting of cells

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A Hybrid Algorithm for Dense Stereo Correspondences in Challenging Indoor Scenes

A Hybrid Algorithm for Dense Stereo Correspondences in Chall...

引用

IEEE International conference on Imaging systems and Techniques (IST) / IEEE International School on Imaging

作者： Georgousis, Stavros Stentoumis, Christos Doulamis, Nikolaos Voulodimos, Athanasios Natl Tech Univ Athens 9 Iroon Polytech Str GR-15773 Athens Greece

ISBN: (纸本)9781509018178

The algorithms for dense correspondences in stereo images are an extensively researched topic, since it is an essential step in a large number of applications. Despite the fact that the first stereo matching algorithms were proposed some decades ago, novel approaches regarding typical, but also cutting-edge applications, are always in demand. Stereo matching is an inverse, ill-posed problem, which usually depends on the application and the scenario. In this contribution, a hybrid approach for stereo matching is proposed, which is based on graph-cuts optimization (global) and cross-based aggregation (local) under a hierarchical scheme. It is shown that the combined effect of a global method in a coarse layer and a local method in finer layers improves the matching results. This hybrid approach exploits the strengths and ameliorates the weaknesses of the individual global and local algorithms. The resulted disparity map is robust without outliers even in untextured areas and at the same time high fidelity details are accurately represented. This hybrid scheme is evaluated on challenging indoor datasets. It is also computationally efficient for applying it on low-processing power applications.

关键词： stereo vision image matching image reconstruction pattern matching

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Real-time Combustion State Identification via image processing: A Dynamic Data-Driven approach

Real-time Combustion State Identification via Image Processi...

引用

American Control conference (ACC)

作者： Hauser, Michael Li, Yue Li, Jihang Ray, Asok Penn State Univ Mech & Nucl Engn Dept University Pk PA 16802 USA

ISBN: (纸本)9781467386821

This paper proposes a framework for analyzing video of physical processes as a paradigm of dynamic data-driven application systems (DDDAS). The algorithms were tested on a combustion system under fuel lean and ultra-lean conditions. The main challenge here is to develop feature extraction and information compression algorithms with low computational complexity such that they can be applied to real-time analysis of video captured by a high-speed camera. In the proposed method, image frames of the video is compressed into a sequence of image features. then, these image features are mapped to a sequence of symbols by partitioning of the feature space. Finally, a special class of probabilistic finite state automata (PFSA), called D-Markov machines, are constructed from the symbol strings to extract pertinent features representing the embedded dynamic characteristics of the physical process. This paper compares the performance and efficiency of three image feature extraction algorithms: Histogram of Oriented Gradients, Gabor Wavelets, and Fractal Dimension. The k-means clustering algorithm has been used for feature space partitioning. The proposed algorithm has been validated on experimental data in a laboratory environment combustor with a single fuel-injector.

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Depth Modeling Modes Complexity Control System for the 3D-HEVC Video Encoder

Depth Modeling Modes Complexity Control System for the 3D-HE...

引用

European Signal processing conference

作者： Gustavo Sanchez Mario Saldanha Luciano Agostini Cesar Marcon Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil IF Farroupilha Alegrete Brazil Federal University of Pelotas Pelotas Brazil

This paper presents a complexity control system for depth maps intra-frame prediction of the 3D-High Efficiency Video Coding (3D-HEVC) standard. The proposed system uses a Proportional-Integral-Derivative controller over the Simplified Edge Detector heuristic to skip the Depth Modeling Modes (DMMs) evaluation dynamically according to a defined target rate. When analyzing the proposed system under Common Test Conditions, the proposed controller stabilizes the system to the target rate (i.e., the percentage of DMMs evaluation) after encoding a few frames, with negligible encoding efficiency impacts. The BD-rate degradation varies from 0.50% to 0.20%, on average, when the target rates vary from 5% to 15%. These target rates imply in an aggressive reduction in the DMMs evaluations, skipping the DMMs from 85% to 95% of the cases.

关键词： Encoding Complexity theory Control systems image edge detection Signal processing algorithms Standards Three-dimensional displays

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The Development of Markov Random Field Theory and Applications on image Segmentation Algorithm

The Development of Markov Random Field Theory and Applicatio...

引用

International conference on Communication and Electronics systems (ICCES)

作者： Zhang, Renqian Huang, Yuru Fu, Sirui Fudan Univ Renqian Zhang Elect Engn Informat Dept Shanghai Peoples R China Beijing Univ Technol Beijing Peoples R China Lanzhou Univ Lanzhou Peoples R China

ISBN: (纸本)9781509010660

image segmentation algorithm is to divide the images into several regions with specific and unique characteristics, and is an important technology to extract the interested target. image segmentation is the key step to realize the research from general image processing into image analysis, and is vital preprocessing method of image recognition and computer vision. We cannot obtain correct recognition if we do not have correct segmentation. Nevertheless, the only basis of segmentation process is brightness or color of pixels in an image. In the processing of computer automatic segmentation, we experience several problems, such as uneven illumination, effect of noise, indistinct part in image, and shadow, and these factors may cause false segmentation. In order to overcome the disadvantages of the traditional segmentation algorithm, in this paper, we propose a novel segmentation algorithm based on Markov Random Field. The segmentation algorithm proposed in this paper is based on Markov Random Field Mode and Bayesian theory, and we determine the objective function in image segmentation problem on the basis of optimality criterion of statistical decision and estimation theory. Some optimization algorithms are used to obtain the maximum possible distribution of Markov Random Field which satisfy these conditions. The experimental result reflects the effectiveness and robustness of our algorithm. As a supplement, we analyze the development trend of the Markov Random Field theory.

关键词： Markov Random Field image segmentation Bayesian theory mathematical optimization algorithm design

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IVOVO: A new interval-valued one-vs-one approach for multi-class classification problems

IVOVO: A new interval-valued one-vs-one approach for multi-c...

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Joint World Congress of International Fuzzy systems Association and International conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Mikel Elkano Mikel Galar Jose Sanz Giancarlo Lucca Humberto Bustince Institute of Smart Cities Public University of Navarre Pamplona Spain

ISBN: (纸本)9781509049189

Decomposition strategies have been shown to be a successful methodology to tackle multi-class classification problems. Among them, One-vs-One approach is a commonly used technique that consists in dividing the original multi-class problem into easier-to-solve binary sub-problems considering each possible pair of classes. However, this methodology is limited to those classifiers returning a single real value for each prediction. In this work, we present a new One-vs-One approach that is able to deal with interval-valued outputs. In order to achieve this goal, we propose applying a normalization method for intervals along with the corresponding extension of three different aggregation strategies: voting, weighted voting, and WinWV. The experimental results show the suitability of the normalization method and the improvement obtained by One-vs-One with respect to a state-of-the-art interval-valued Fuzzy Rule-Based Classification System (IVTURS).

关键词： Pragmatics Training Fuzzy sets Signal to noise ratio image processing Classification algorithms Uncertainty

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