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Blind background subtraction in dental panoramic X-ray images: An application approach

Blind background subtraction in dental panoramic X-ray image...

引用

27th DAGM (German Association for pattern recognition) Symposium, DAGM 2005

作者： Goebel, Peter Michael Belbachir, Nabil Ahmed Truppe, Michael Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Austria Fh-campus Wien Technical Project- and Processmanagement Austria Karl Landsteiner Institute for Biotelematics Danube University Krems Austria

Dental Panoramic X-ray images are images having complex content, because several layers of tissue, bone, fat, etc. are superimposed. Non-uniform illumination, stemming from the X-ray source, gives extra modulation to the image, which causes spatially varying X-ray photon density. The interaction of the X-ray photons with the density of matter causes spatially coherent varying noise contribution. Many algorithms exist to compensate background effects, by pixel based or global methods. However, if the image is contaminated by a non-negligible amount of noise, that is usually non-Gaussian, the methods cannot approximate the background efficiently. In this paper, a dedicated approach for background subtraction is presented, which operates blind, that means the separation of a set of independent signals from a set of mixed signals, with at least, only little a priori information about the nature of the signals, using the A-Trous multiresolution transform to alleviate this problem. The new method estimates the background bias from a reference scan, which is taken without a patient. The background values are rescaled by a polynomial compensation factor, given by mean square error criteria, thus subtracting the background will not produce additional artifacts in the image. The energy of the background estimate is subtracted from the energy of the mixture. The method is capable to remove spatially varying noise also, allocating an appropriate spatially noise estimate. This approach has been tested on 50 images from a database of panoramic X-ray images, where the results are cross validated by medical experts. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Medical imaging

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Evaluation of object tracking for aircraft activity surveillance

Evaluation of object tracking for aircraft activity surveill...

引用

Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance

作者： D. Thirde M. Borg J. Aguilera J. Ferryman K. Baker M. Kampel Computational Vision Group University of Reading UK Pattern Recognition and Image Processing Group University of Technology Vienna Austria

This paper presents the evaluation of an object tracking system that has been developed in the context of aircraft activity monitoring. The overall tracking system comprises three main modules - motion detection, object tracking and data fusion. In this paper we primarily focus on performance evaluation of the object tracking module, with emphasis given to the general 2D tracking performance and the 3D object localisation.

关键词： Aircraft Surveillance Tracking Motion detection Layout Karhunen-Loeve transforms Computer vision Object detection pattern recognition image processing

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Human Activity recognition with User-Free Accelerometers in the Sensor Networks

Human Activity Recognition with User-Free Accelerometers in ...

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2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Shuangquan Wang Jie Yang Ningjiang Chen Xin Chen Qinfeng Zhang Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Philips Research East Asia

Many applications using wireless sensor networks (WSNs) aim at providing friendly and intelligent services based on the recognition of human's *** the research result on wearable computing has been fruitful,our experience indicates that a user-free sensor deployment is more natural and acceptable to *** our system,activities were recognized through matching the movement patterns of the objects,which tri-axial accelerometers had been attached to. Several representative features,including accelerations and their fusion,were calculated and three classifiers were tested on these *** with Decision Tree(DT) C4.5 and Multiple-Layer Perception(MLP),Support Vector Machine (SVM) performs relatively well across different tests. Additionally,feature selection will be discussed for better system performance for WSNs.

关键词： Human Activity recognition with User-Free Accelerometers in the Sensor Networks Sensor Activity

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Investigation on traditional and modern ceramic documentation

Investigation on traditional and modern ceramic documentatio...

引用

IEEE International Conference on image processing

作者： M. Kampel H. Mara R. Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Vienna Austria

Archaeology is at a point where it can benefit greatly from the application of computer vision methods, and in turn provides a large number of new, challenging and interesting conceptual problems and data for computer science. This is true in particular in the study of ceramics - the most abundant and widespread of all archaeological finds. The traditional way of documenting archaeological sherds is to draw the profile line, which is the intersection of a sherd along the axis of symmetry. A profilograph is a mechanical device, which can directly acquire and transfer a profile line by pin-pointing the profile on a sherd to a computer. We developed a fully automated vision system, which is able to compute the profile line out of the acquired 3D model of the fragment. In this paper we want to give a thorough comparison between the traditional manual approach, the profilograph and our system and present an improvement of the robustness of our approach by finding circular rills on the fragments. Practical experiments have been undertaken at the excavation Tel Dor in Israel.

关键词： Ceramics Documentation Computer vision Pins pattern recognition image processing Automation Application software Computer science Machine vision

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Evaluation of Motion Segmentation Quality for Aircraft Activity Surveillance

Evaluation of Motion Segmentation Quality for Aircraft Activ...

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Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance

作者： J. Aguilera H. Wildenauer M. Kampel M. Borg D. Thirde J. Ferryman Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Computational Vision Group University of Reading Reading UK

Recent interest has been shown in performance evaluation of visual surveillance systems. The main purpose of performance evaluation on computer vision systems is the statistical testing and tuning in order to improve algorithm's reliability and robustness. In this paper we investigate the use of empirical discrepancy metrics for quantitative analysis of motion segmentation algorithms. We are concerned with the case of visual surveillance on an airport's apron, that is the area where aircrafts are parked and serviced by specialized ground support vehicles. Robust detection of individuals and vehicles is of major concern for the purpose of tracking objects and understanding the scene. In this paper, different discrepancy metrics for motion segmentation evaluation are illustrated and used to assess the performance of three motion segmentors on video sequences of an airport's apron.

关键词： Motion segmentation Computer vision Aircraft Surveillance Robustness Statistical analysis Algorithm design and analysis Ground support Land vehicles Road vehicles

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A robust, real-time voice activity detection algorithm for embedded mobile devices

A robust, real-time voice activity detection algorithm for e...

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作者： Wu, Bian Ren, Xiaolin Liu, Chongqing Zhang, Yaxin Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China Motorola Labs. China Research Center 38F CITIC Sq. 1168 Nanjing Rd. W. Shanghai 200041 China

When an Automatic Speech recognition (ASR) system is applied in noisy environments, Voice Activity Detection (VAD) is crucial to the performance of the overall system. The employment of the VAD for ASR on embedded mobile systems will minimize physical distractions and make the system convenient to use. Conventional VAD algorithm is of high complexity, which makes it unsuitable for embedded mobile devices;or of low robustness, which holds back its application in mobile noisy environments. In this paper, we propose a robust VAD algorithm specifically designed for ASR on embedded mobile devices. The architecture of the proposed algorithm is based on a two-level decision making strategy, where there is an interaction between a lower features-based level and subsequent decision logic based on a finite-state machine. Many discriminating features are employed in the lower level to improve the robustness of the VAD. The two-level decision strategy allows different features to be used in different states and reduces the cost of the algorithm, which makes the proposed algorithm suitable for embedded mobile devices. The evaluation experiments show the proposed VAD algorithm is robust and contribute to the overall performance gain of the ASR system in various acoustic environments. © 2005 Springer Science+Business Media, Inc.

关键词： Speech recognition

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Pedestrian Tracking Based on Colour and Spatial Information

Pedestrian Tracking Based on Colour and Spatial Information

引用

Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： F.H. Seitner B.C. Lovell Pattern Recognition and Image Processing Group University of Technology Vienna Austria National ICT Australia and School of ITEE University of Queensland Australia

This paper describes a tracking with appearance modelling system for pedestrians. A cascade of boosted classifiers and Haar-like rectangular features [6, 12] are used for the pedestrian detection. Statistical modelling in the HSV colour space is used for adaptive background modelling and subtraction, where the use of circular statistics for hue is proposed. By using the background model in combination with the detector, the system extracts a feature vector based on colour statistics and the spatial information. Circular [9] and linear statistics are applied on the extracted features to robustly track the pedestrians and other moving objects through the scene. An adaptive appearance model copes with partial or full occlusions and addresses the problem of missing or wrong detections in single frames.

关键词： Statistics Data mining Feature extraction image color analysis Detectors pattern recognition image processing Australia Vectors Robustness

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Line-based landmark recognition for self-localization of soccer robots

Line-based landmark recognition for self-localization of soc...

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International Conference on Emerging Technologies, ICET

作者： A. Baist R. Sablatnig G. Novak Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria Institute of Computer Technology Vienna University of Technology Vienna Austria

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Noise estimation in panoramic x-ray images: an application analysis approach

Noise estimation in panoramic x-ray images: an application a...

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IEEE/SP Workshop on Statistical Signal processing (SSP)

作者： P.M. Goebel A.N. Belbachir M. Truppe Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Karl Landsteiner Institute for Biotelematics Danube-University of Krems Krems Austria

This paper presents an appropriate approach for the robust estimation of the noise statistics in dental panoramic X-ray images. To achieve maximum image quality after denoising, a semi-empirical scatter model is presented, leading to a local adaptive Gaussian scale mixture (GSM) model. State of the art methods use multiscale filtering of images to reduce the irrelevant part of information, based on generic estimation of noise. The usual assumption of a distribution of Gaussian and Poisson statistics only leads to overestimation of the noise variance in regions of low intensity (small photon counts), but to underestimation in regions of high intensity and therefore to non-optimal results. The analysis approach is tested on a database of 50 panoramic X-ray images and the results are cross-validated by medical experts. It is shown that the local standard deviation (SDEV) in images, stemming from homogeneous phantoms (AI, PMMA), follows a generalized Nakagami distribution (GND). The heavily tailed distribution is not covered entirely by the GND. The error density function, is hypothesized to stem from scatter-glare, degrading the image. A beam stop method, for estimation of the scatter-glare amount, verifies that hypothesis. Finally, the application of the method for a phantom image, is shown with denoising results for comparison purpose, followed by the conclusion

关键词： X-ray imaging image analysis Noise reduction Electromagnetic scattering Particle scattering X-ray scattering Imaging phantoms Noise robustness Statistics Dentistry

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A robust matching algorithm for active appearance models 1

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2005 - Workshop on image processing for Medicine: Algorithms - Systems - Applications, BVM 2005

作者： Beichel, Reinhard Bischof, Horst Langs, Georg Sonka, Milan Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16/2 A-8010 Graz Austria Pattern Recognition and Image Processing Group Vienna University of Technology Favoritenstr. 9 A-1040 Vienna Austria Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 United States

ISBN: (数字)9783540264316

ISBN: (纸本)3540250522

This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing model and image appearance, and modes of the residual are analyzed. Second, all possible mode combinations are tested by evaluating an objective function. The objective function allows the selection of an outlier-free mode combination. Experiments demonstrate the ability of the robust matching method to successfully cope with outliers - compared to standard AAM matching, no degeneration of the model during matching occurs.

关键词： Statistics

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