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Adaptive Silhouette Extraction in Dynamic Environments Using Fuzzy Logic

Adaptive Silhouette Extraction in Dynamic Environments Using...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： xi Chen Zhihai He J.M. Keller D. Anderson M. Skubic Department of Electrical and Computer Engineering University of Missouri Columbia MO USA

Extracting a human silhouette from an image is the enabling step for many high-level vision processing tasks, such as human tracking and activity analysis. Although there are a number of silhouette extraction algorithms proposed in the literature, most approaches work efficiently only in constrained environments where the background is relatively simple and static. In a previous paper, we addressed some of the challenges in silhouette extraction and human tracking in a real-world unconstrained environment where the background is complex and dynamic. We extracted features from image regions, accumulated the feature information over time, fused high-level knowledge with low-level features, and built a time-varying background model. A problem with our system is that by adapting the background model, objects moved by a human are difficult to handle. In order to reinsert them into the background, we run the risk of cutting off part of the human silhouette, such as in a quick arm movement. In this paper, we develop a fuzzy logic inference system to detach the silhouette of a moving object from the human body. Our experimental results demonstrate that the fuzzy inference system is very efficient and robust.

关键词： Fuzzy logic Humans Data mining Biological system modeling Robustness Hidden Markov models Feature extraction Layout Target tracking Vehicle dynamics

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Pervasive surveillance using a cooperative mobile sensor network

Pervasive surveillance using a cooperative mobile sensor net...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： M. Huntwork A. Goradia Ning xi C. Haffner C. Klochko M. Mutka Department of Electrical and Computer Engineering Michigan State University East Lansing MI USA Department of Computer Science and Engineering Michigan State University East Lansing MI USA

A distributed processing and communication approach is applied to networked surveillance systems providing an extended perception and sensing capability in monitored environments. By pervasive we mean that the entire surveyed area is covered by a heterogeneous collection of fixed and mobile sensors. The sensor network uses a cooperative tracking technique that allows for the deployment of mobile sensors based on data provided by other sensors in the network. Also, an image-based tracking technique is used for tracking when the target is in view. The task of tracking multiple targets in a distributed surveillance network is a challenging problem because of the following reasons: (1) multiple targets need to be monitored and tracked continuously and must remain in view of at least one of the sensors; (2) the view of the sensors needs to be optimized so that the targets are observed with a discernible resolution for feature identification; (3) it is important to devise stable control algorithms for accomplishing the surveillance task; (4) assigning tracking tasks to sensors must consider load balancing and efficient use of all sensors. This paper presents a distributed communication and processing model that allows for a fast deployment of sensor nodes and implementation of ad hoc tracking in a multi-target surveillance scenario. Also, experimental results demonstrate the efficacy of the proposed approach for tracking multiple targets over a large area with fixed and mobile sensors

关键词： Surveillance Target tracking Monitoring Sensor systems Mobile communication Wireless sensor networks Intelligent sensors Security Safety Computer science

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A set theoretic approach to object-based image restoration

A set theoretic approach to object-based image restoration

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Conference on image processing - algorithms and systems IV

作者： Fan, X Huang, H Qi, C Liang, D Xi An Jiao Tong Univ Inst Image Proc & Recognit Xian 710049 Peoples R China

ISBN: (纸本)0819456454

The approaches that analyze local characteristics of an image to impose constraints are prevailing in image restoration, but they are less effective in the cases of severe degradation and wavy noise corruption. In this paper, we incorporate the common characteristics that the images of a class of objects present into image restoration, termed as object-based image restoration. The characteristics are represented as deterministic sets, which is combined with the set describing the image degradation model in a set theoretic formulation. A parllel subgradient projection algorithm is applied to find the solution in the intersection of these sets. Experiments performed on frontal face images show the improved performance of the approach in both mentioned cases, by comparing with local analysis based algorithms. With the concise formulation and the efficient algorithm, the object-based restoration can be implemented with ease and resolved with less complexity.

关键词： image restoration set theoretic formulation object principal component analysis parallel subgradient projection

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Design and performance of the civil air patrol ARCHER hyperspectral processing system

Design and performance of the civil air patrol ARCHER hypers...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery xi

作者： Stevenson, B O'Connor, R Kendall, W Stocker, A Schaff, W Alexa, D Salvador, J Eismann, M Barnard, K Kershenstein, J Space Computer Corp. (United States) Civil Air Patrol (United States) Air Force Research Lab. (United States) Naval Research Lab. (United States)

ISBN: (纸本)0819457914

The Civil Air Patrol (CAP) is procuring Airborne Real-time Cueing Hyperspectral Enhanced Reconnaissance (ARCHER) systems to increase their search-and-rescue mission capability. These systems are being installed on a fleet of Gippsland GA-8 aircraft, and will position CAP to gain real-world mission experience with the application of hyperspectral sensor and processing technology to search and rescue. The ARCHER system design, data processing, and operational concept leverage several years of investment in hyperspectral technology research and airborne system demonstration programs by the Naval Research Laboratory (NRL) and Air Force Research Laboratory (AFRL). Each ARCHER system consists of a NovaSol-designed, pushbroom, visible/near-infrared (VNIR) hyperspectral imaging (HSI) sensor, a co-boresighted visible panchromatic high-resolution imaging (HRI) sensor, and a CMIGITS-III GPS/INS unit in an integrated sensor assembly mounted inside the GA8 cabin. ARCHER incorporates an on-board data processing system developed by Space Computer Corporation (SCC) to perform numerous real-time processing functions including data acquisition and recording, raw data correction, target detection, cueing and chipping, precision image geo-registration, and display and dissemination of image products and target cue information. A ground processing station is provided for post-flight data playback and analysis. This paper describes the requirements and architecture of the ARCHER system, with emphasis on data processor design, components, software, interfaces, and displays. Key sensor performance characteristics and real-time data processing features are discussed. The use of the system for detecting and geo-locating ground targets in real-time is demonstrated using test data collected in Southern California in the fall of 2004.

关键词： Sensors Target detection image processing Cameras Data processing image sensors Imaging systems Data acquisition Detection and tracking algorithms Hyperspectral imaging

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Hyperspectral image sharpening using multispectral data

Hyperspectral image sharpening using multispectral data

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery xi

作者： Winter, ME Winter, EM Beaven, SG Ratkowski, AJ Univ Hawaii Manoa Honolulu HI 96822 USA

ISBN: (纸本)0819457914

Multispectral sharpening of hyperspectral imagery fuses the spectral content of a hyperspectral image with the spatial and spectral content of the multispectral image. The approach we have been investigating compares the spectral information present in the multispectral image to the spectral content in the hyperspectral image and derives a set of equations to approximately transform the multispectral image into a synthetic hyperspectral image. This synthetic hyperspectral image is then recombined with the original low-resolution hyperspectral image to produce a sharpened product. We evaluate this technique against several types of data, showing good performance across with all data sets. Recent improvements in the algorithm allow target detection to be performed without loss of performance even at extreme sharpening ratios.

关键词： Hyperspectral imaging Sensors Spatial resolution image filtering Target detection Multispectral imaging Vegetation image processing Imaging systems Data modeling

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Genie pro: Robust image classification using shape, texture and spectral information

Genie pro: Robust image classification using shape, texture ...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery xi

作者： Perkins, S Edlund, K Esch-Mosher, D Eads, D Harvey, N Brumby, S Los Alamos Natl Lab Los Alamos NM 87545 USA

ISBN: (纸本)0819457914

We present Genie Pro, a new software tool for image analysis produced by the ISIS (Intelligent Search in images and Signals) group at Los Alamos National Laboratory. Like the earlier GENIE tool produced by the same group, Genie Pro is a general purpose adaptive tool that derives automatic pixel classification algorithms for satellite/aerial imagery, from training input provided by a human expert. Genie Pro is a complete rewrite of our earlier work that incorporates many new ideas and concepts. In particular, the new software integrates spectral information;and spatial cues such as texture, local morphology and large-scale shape information;in a much more sophisticated way. In addition, attention has been paid to how the human expert interacts with the software: Genie Pro facilitates highly efficient training through an interactive and iterative "training dialog". Finally, the new software runs on both Linux and Windows platforms, increasing its versatility. We give detailed descriptions of the new techniques and ideas in Genie Pro, and summarize the results of a recent evaluation of the software.

关键词： image analysis image processing image classification Roads Evolutionary algorithms Earth observing sensors Satellite imaging Satellites Geographic information systems Hyperspectral imaging

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Geometrically robust image watermarking based on image normalization

Geometrically robust image watermarking based on image norma...

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2005 International Symposium on Intelligent Signal processing and Communication systems, ISPACS 2005

作者： Song, Qi Zhu, Guang-xi Luo, Hang-Jian Dept. of El Huazhong University of Science and Technology Wuhan 430074 China Wuhan Hongxin Telecommunication Technologies Co. Ltd Wuhan 430070 China

ISBN: (纸本)0780392663

In image watermarking, geometric transformations are among the most challenging problems. Moment based image normalization has been used in watermarking. Embedding the watermark into the normalized image is the idea of this kind of algorithms. However, because the sizes of the normalized original image and the normalized geometrically attacked image are different, the synchronization of the embedding and the extracting is very difficult to be guaranteed. In this paper, we propose a watermarking algorithm based on image normalization. We choose a parameter in the normalized image as the watermark. And the watermarked image is the combination of the original image and a weighted nonlinear transformation of the original. Watermark detection is as simple as computing the parameter of the normalized version of the received image. The proposed algorithm has proved to be robust to many kinds of geometric manipulations that are performed as part of StirMark attacks. © 2005 IEEE.

关键词： Digital watermarking

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An efficient method to evaluate fusion performance of remote sensing image

An efficient method to evaluate fusion performance of remote...

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MIPPR 2005: image Analysis Techniques

作者： Li, xiaochun Chen, Jing National Defence Key Laboratory of Blind Processing of Signals 610041Chendu China The Telecommunication Engineering Institute AFEU 710077 Xi'an China

With the development of image fusion technologies, it is necessary to look for objective evaluation methods of image fusion, which may offer guidance for computer to select automatically appropriate fusion algorithms under different scenes. This paper consists of three part: First, current evaluation methods of image fusion are classified as four kinds, such as methods based on statistical characteristic, methods based on definition, methods based on information theory, and methods based on important feature factors. At the same time, all methods are analyzed and compared in the case of validity, redundancy, and consistency of algorithms when evaluate fusion effects. Second, on the basis of analysis and compare of evaluation methods above, some evaluation parameters are picked out, which have advantage over others on objectivity and validity, and reflect different evaluation performances for fusion algorithms. Therefore, based on voting ideas, a method for overall evaluation of fusion algorithms is proposed by using evaluation parameters selected above. Finally, overall evaluation method proposed is applied to evaluate fusion results of different remote sensing images and different fusion algorithms. Simulation results show that the method proposed in this paper is accurate, objective and very effective for evaluating performance of image fusion, and evaluation results are in accordance with subjective evaluation results by direct look.

关键词： Imaging systems

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Geometrically robust image watermarking based on image normalization

Geometrically robust image watermarking based on image norma...

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IEEE International Symposium on Intelligent Signal processing and Communication systems (ISPACS)

作者： Qi Song Guang-xi Zhu Hang-jian Luo Department of EI Huazhong University of Science and Technology Wuhan China Wuhan Hongxin Telecommunication Technologies Company Limited Wuhan China

关键词： Watermarking Resists Noise robustness Protection Filtering algorithms Fourier transforms Discrete Fourier transforms Computer vision Pattern recognition image analysis

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Updating algorithm for extracting the basis of karhunen-loeve transform in non-zero mean data

Updating algorithm for extracting the basis of karhunen-loev...

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2004 7th International Conference on Signal processing Proceedings, ICSP

作者： Yanyun, Qu Nanning, Zheng Cuihua, Li Zejian, Yuan Inst. of Artif. Intell. and Robotics Xi'an Jiaotong University Xi'an 710049 China Department of Computer Science Xiamen University Xiamen 361005 China

ISBN: (纸本)0780384075

Karhunen-Loeve transform (KLT) is a popular method for dimensional reduction and feature extraction in image analysis, signal processing and automatic control systems, and so on. The drawback of the KLT is expensive computation. So the efficient updating algorithms were proposed in signal processing and numerical linear algebra. The updating algorithms make the active learning and recognition possible. But they mainly deal with zero mean data. In this paper, we propose an updating algorithm for KLT for non-zero mean data. And we also show its application in face analysis. The experimental results demonstrate the efficiency of our algorithm.

关键词： Feature extraction

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