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International conference on Signal processing Proceedings (ICSP)

作者： Wang Zhenhua Xu Hongbo Tian Yan Tian Jinwen Liu Jian Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Image Processing and Intelligent Control Huazhong University of science and Technology Wuhan China

ISBN: (纸本)0780374886

With the development of remote sensing technique, onboard data compression has become an urgent need and a lot of study has been directed toward the development of efficient techniques. In this paper, the construction approach of integer Haar is discussed briefly, and a simple image compression scheme based on the integer Haar wavelet transform and block DPCM is proposed. The scheme can be easily designed for data processing in real-time systems of remote sensing with parallel algorithms. Simulation experimental results demonstrate that the proposed approach is a efficient image compression method.

关键词： image coding remote sensing Wavelet transforms Frequency Data compression image reconstruction pattern recognition Artificial intelligence image processing Intelligent control

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24th DAGM Symposium on pattern recognition, 2002

24th DAGM Symposium on Pattern Recognition, 2002

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24th German Association for pattern recognition Symposium, DAGM 2002

ISBN: (纸本)354044209X

The proceedings contain 74 papers. The special focus in this conference is on Tracking, Segmentation, 3D Shape and Optical Flow. The topics include: Multimodal shape tracking with point distribution models;on optimal camera parameter selection in kalman filter based object tracking;video-based handsign recognition for intuitive human-computer-interaction;quality enhancement of reconstructed 3d models using coplanarity and constraints;human body reconstruction from image sequences;a knowledge-based system for context dependent evaluation of remote sensing data;empirically convergent adaptive estimation of grayvalue structure tensors;fast ICP algorithms for shape registration;appearance based generic object modeling and recognition using probabilistic principal component analysis;logarithmic tapering graph pyramid;a new and efficient algorithm for detecting the corners in digital images;unsupervised image partitioning with semidefinite programming;the application of genetic algorithms in structural seismic image interpretation;efficient modification of the central weighted vector median filter;fast recovery of piled deformable objects using superquadrics;analysis of amperometric biosensor curves using hidden-Markov-modells;unifying registration and segmentation for multi-sensor images;relations between soft wavelet shrinkage and total variation denoising;statistical image sequence processing for temporal change detection;shape from single stripe pattern illumination;a probabilistic approach to building roof reconstruction using semantic labelling;adaptive pose estimation for different corresponding entities;properties of a three-dimensional island hierarchy for segmentation of 3d images with the color structure code and hierarchical primitives based contour matching.

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Thresholding video images for text detection

Thresholding video images for text detection

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作者： Du, Eliza Yingzi Chang, Chein-I Thouin, Paul D. Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle Baltimore MD 21250 Department of Defense Fort Meade MD 20755

Thresholdging video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding methods that work well for document images may not work effectively for video images in some applications. This paper investigates the issue of thresholding video images for text detection and further develops a relative entropy-based thresholding approach that can effectively extract text from complicated video images. In order to demonstrate its performance a comparative study is conducted among the proposed thresholding method and several thresholding techniques which are widely used for document and gray scale images. The experimental results show that thresholdging video images is far more difficult than thresholding document images and simple histogram-based methods generally do not perform well. © 2002 IEEE.

关键词： Video signal processing

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Entropy optimized contrast stretch to enhance remote sensing imagery

Entropy optimized contrast stretch to enhance remote sensing...

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International conference on pattern recognition

作者： Xiaoyin Xu E.L. Miller Center for Subsurface Sensing and Imaging Systems Department of ECE Northeastern University Boston MA USA

This paper presents a contrast stretch (CS) method based on minimum entropy constraint to enhance images obtained in remote sensing applications such as ground penetrating radar (GPR), synthetic aperture radar, and infra-red imagery. The CS enhances contrast of the low-contrast part of an image. In remote sensing, it is usually the desirable signals that are of low contrast while interference of high contrast. The CS modifies the original image such that pixel values above and below preset boundaries are set to Zero and the maximum possible pixel value and the pixel values falling between the boundaries are stretched out to enhance the contrast of the image. Using the CS we can enhance the contrast of desirable signals from, for example, a buried landmine or an object obscured by some interference. On the other hand, the CS inevitably enhances other parts of a remote sensing images, such as clutter and measurement noise. Therefore there is a trade-off in using the CS. It is beneficial to find the correct "cut-off" boundaries in the CS in some optimal sense. We propose using minimum entropy as a criterion of looking for the optimal CS parameter Using field data from GPR application, we show that improved image can be obtained which makes further processing such as detection more accurate.

关键词： Entropy remote sensing Ground penetrating radar Clutter Interference Sensor arrays Reflection Pixel Landmine detection Noise measurement

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Thresholding video images for text detection

Thresholding video images for text detection

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International conference on pattern recognition

作者： E.Y. Du Chang C P.D. Thouin Remote Sensing Signal and Image Processing Laboratory. Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD USA Department of Defense Fort Meade MD USA

Thresholding video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding methods that work well for document images may not work effectively for video images in some applications. This paper investigates the issue of thresholding video images for text detection and further develops a relative entropy-based thresholding approach that can effectively extract text from complicated video images. In order to demonstrate its performance a comparative study is conducted among the proposed thresholding method and several thresholding techniques which are widely used for document and gray scale images. The experimental results show that thresholding video images is far more difficult than thresholding document images and simple histogram-based methods generally do not perform well.

关键词： Entropy Shape measurement image resolution Information retrieval image retrieval Particle measurements remote sensing Signal processing image processing Laboratories

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A target detection method in Range-Doppler domain from SAR echo data

Proceedings - International Conference on Pattern Recognitio...

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Proceedings - International conference on pattern recognition 2002年第1期16卷 91-94页

作者： Liming, Lu Runsheng, Wang Wugao, Li ATR National Lab. National University of Defense Technology Changsha Hunan 410073 China Jiangnan Institute of Remote Sensing Shanghai 200072 China

The direct evidence of Radar Target recognition is the backscatter energy and its distribution of objects, which is concluded by imaging process of Synthetic Aperture Radar (SAR) in the two-dimension image domain. So the issues about Automatic Target recognition (ATR) of SAR are often a "post- process" following SAR imaging. A method of target detection in the state of non-imaging based on analyzing the features of all kinds of targets on SAR echo data is presented in this paper, where the targets are detected in Range-Doppler domain (RDD). Based on analysis of target features in RDD, an algorithm of target detection in a RDD image is developed. The experimental results indicate the validity of the algorithm for special kinds of target detection. The algorithm is simple, able to recurrent, easy for real-time processing and hardware implementation. It can also apply to getting target alarm with real-time SAR data for the pre-selected targets and do the imaging process selectively at the same time. © 2002 IEEE.

关键词： Radar target recognition

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A target detection method in range-Doppler domain from SAR echo data

A target detection method in range-Doppler domain from SAR e...

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International conference on pattern recognition

作者： Liming Lu Runsheng Wang Li. Wugao ATR National Lab National University of Defense Technology Changsha Hunan P.R.China

ISBN: (纸本)076951695X

The direct evidence of radar target recognition is the backscatter energy and its distribution of objects, which is concluded by the imaging process of synthetic aperture radar (SAR) in a two-dimension image domain. Thus, the issues about automatic target recognition of SAR are often a "post-process" following SAR imaging. A method of target detection in the state of non-imaging based on analyzing the features of all kinds of targets on SAR echo data is presented in this paper, where the targets are defected in range-Doppler domain (RDD). Based on the analysis of target features in RDD, an algorithm of target detection in a RDD image is developed. The experimental results indicate the validity of the algorithm for special kinds of target detection. The algorithm is simple, able to recurrent, easy for real-time processing and hardware implementation. It can also be applied to getting target alarm with real-time SAR data for the pre-selected targets and do the imaging process selectively at the same time.

关键词： Object detection Target recognition Radar imaging Radar scattering Spaceborne radar Chirp modulation Radar remote sensing Radar polarimetry Frequency conversion remote sensing

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Multiscale watershed segmentation of multivalued images

Multiscale watershed segmentation of multivalued images

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International conference on pattern recognition

作者： P. Scheunders J. Sijbers Vision Lab Department of Physics University of Antwerp Antwerp Belgium

ISBN: (纸本)076951695X

In this paper, a new segmentation technique for multivalued images is elaborated. The technique accesses multiscale edge information of a multivalued image by a concept, called multiscale fundamental form. At different scales, an edge map of the multivalued images is obtained, at which a watershed-based algorithm is applied. The multiscale behavior of the obtained watershed regions is employed to conduct a region merging procedure. In order to remove noise or local texture, prior to segmentation an anisotropic diffusion filter is applied, also making use of the multiscale fundamental forms. In this way, the entire procedure is applied using multivalued processing.

关键词： image segmentation Discrete wavelet transforms Eigenvalues and eigenfunctions Merging Anisotropic magnetoresistance image edge detection Physics remote sensing Nuclear power generation Biomedical imaging

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IEEE CCECE2002. Canadian conference on Electrical and Computer Engineering. conference Proceedings (Cat. No.02CH37373)

IEEE CCECE2002. Canadian Conference on Electrical and Comput...

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Canadian conference on Electrical and Computer Engineering (CCECE)

The following topics are dealt with: power system modelling, planning and operation; power electronics and machines; electromagnetics and optics; antenna theory, design and applications; remote sensing; SAR ; acoustic ranging; microelectronics and VLSI; nanotechnology and micromachining; instrumentation and sensors; circuits and systems; robotics and mechatronics; reliability engineering; computers and digital hardware; real-time systems; software and information technology; computational intelligence; neural networks; genetic algorithms and fuzzy logic; pattern recognition; image processing; video processing; signal processing and filter design; biomedical engineering; health-care systems; communications systems; computer networks; wireless networks; telecommunication traffic analysis; QoS; industrial applications.

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Enhancing the performance of personal identity authentication systems by fusion of face verification experts

Enhancing the performance of personal identity authenticatio...

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IEEE International conference on Multimedia and Expo (ICME)

作者： J. Kittler M. Ballette J. Czyz F. Roli L. Vandendorpe Centre for Vision Speech and Signal Processing University of Surrey Guildford UK Department of Electrical Engineering University of Cagliari Italy Communications and Remote Sensing Laboratory Universite catholique de Louvain Belgium

We investigate the behavior knowledge space method (see Xu, L. et al., IEEE Transactions SMC, vol.22, no.3, p.418-35, 1992) and decision templates method (see Kuncheva, L. et al., pattern recognition, vol.34, p.299-314, 2001) of classifier fusion in the context of face verification. The study involves six experts which are not only correlated, but also their performance levels differ by as much as a factor of three. Through extensive experiments on the XM2VTS database using the Lausanne protocol, we found that the behavior knowledge space fusion strategy achieved consistently better results than the decision templates method. Most importantly, it exhibited quasi monotonic behavior as the number of experts combined increased. This is a very important conclusion, as it means that the performance of the multimodal system is not degraded by adding experts.

关键词： Authentication Biometrics Face detection Protocols image databases Error analysis Expert systems Speech processing Biomedical signal processing remote sensing

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