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

作者： Hyunjong Ki Jeonho Shin Joonki Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)0780386396

This paper proposes a hierarchical approach to the active shape model (ASM) using a wavelet transform. Local structure model fitting in the ASM plays an important role in model-based pose and shape analysis. The proposed algorithm can robustly find good solutions in complex images by using wavelet decomposition. We also describe how to apply Kalman filtering for ASM-based, real-time video tracking. The proposed algorithm has been tested for various sequences containing human motion to demonstrate the improved performance of the proposed object tracking.

关键词： Active shape model Humans Robustness Kalman filters Filtering image analysis image processing intelligent systems Laboratories Multimedia systems

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Enhanced active shape model using evolutionary computation and its extension to RGB color space

Enhanced active shape model using evolutionary computation a...

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

作者： V. Maik Hyunjong Ki Sangjin Kim Jeongho Shin Seongwon Lee L. Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

This paper deals with an application of evolutionary computation to active shape model (ASM) for locating and analyzing objects an image. The ASM algorithm has proved to be a successful method for segmentation of objects in gray-scale images. However, a number of modifications and extensions to the basic ASM algorithm have been proposed to cope up with various limitations. The proposed method in this paper relies on two such extensions: (i) evolutionary algorithm for better local structure model; and (ii) incorporation of color information for solving the outlier problem in model fitting.

关键词： Active shape model Evolutionary computation Humans Biological system modeling Application software Deformable models Robustness Colored noise Noise shaping image processing

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Controlling the false positive detection rate in fuzzy clustering of fMRI data

Controlling the false positive detection rate in fuzzy clust...

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IEEE International Symposium on Biomedical Imaging

作者： H. Jahanian H. Soltanian-Zadeh G.A. Hossein-Zadeh Signal and Image Processing Group School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Elec. Eng. Department Control and Intelligent Processing Center of Excellence University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Health System Detroit MI USA

Despite its potential advantages for fMRI analysis, fuzzy C-means (FCM) clustering suffers from limitations such as the need for a priori knowledge of the number of clusters, and unknown statistical significance and instability of the results. We propose a randomization-based method to control the false positive rate and estimate statistical significance of the FCM results. Using this novel approach, we develop an fMRI activation detection method. The ability of the method in controlling the false positive rate is shown by analysis of false positives in activation maps of resting-state fMRI data. Controlling the false positive rate in FCM allows comparison of different fuzzy clustering methods, using different feature spaces, to other fMRI detection methods. In this paper, using simulation and real fMRI data, we compare a novel feature space that takes the variability of the hemodynamic response function into account (HRF-based feature space) to the conventional cross-correlation analysis and FCM using the cross-correlation feature space.

关键词： Fuzzy control Clustering methods Hemodynamics Clustering algorithms Brain Signal processing image processing intelligent systems Process control Control systems

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Sigmoidal Function Based Optimal Weighted Vector Directional Filters

Sigmoidal Function Based Optimal Weighted Vector Directional...

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Final Program and Proceedings of the PICS Conference: The Digital Photography Conference

作者： Lukac, Rastislav Stachowicz, Marian S. Slovak Image Processing Center Jarkova 343 049 25 Dobsina Slovakia Laboratory for Intelligent Systems Department of Electrical Engineering University of Minnesota Duluth 10 University Drive Duluth MN 55812 United States

In this paper, we provide a new directional optimization of a recently developed class of weighted vector directional filters (WVDFs) that represent a powerful tool for removing impulsive noise, bit errors and color artifacts in color images. Depending on the weight coefficients, the WVDFs can be designed to perform a wide range of smoothing operations. The proposed optimization process based on sigmoidal approximation of the sign function and utilizing local information allows to adapt the WVDF behavior to statistical properties of both noise and useful signal, saves the memory space and is easy to implement. The proposed sigmoidal function based optimal WVDFs find the application in denoising of standard color images and digitized old color photos, they are able to remove impulsive noise and outliers, and provide excellent signal-detail and color chromaticity preservation.

关键词： Color image processing

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Wavelet based estimation of the fractal dimension in fBm images

Wavelet based estimation of the fractal dimension in fBm ima...

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International IEEE/EMBS Conference on Neural Engineering, CNE

作者： C. Parra K. Iftekharuddin D. Rendon Intelligent Systems and Image Processing Laboratory Department of Electrical and Computer Engineering University of Memphis Memphis TN USA

Fractional Brownian Motion (fBm) has been successfully exploited to model an important number of physical phenomena and non-stationary processes such as medical images. These mathematical models closely describe essential properties of natural phenomena, such as self-similarity, scale invariance and fractal dimension (FD). The use of wavelet analysis combined with fBm analysis may provide an interesting approach to compute key values for fBm processes, such as the fractal dimension FD. We propose two models to calculate the Hurst Coefficient H (and hence FD) for both one-dimensional and two-dimensional signals. The first approach is based on statistical properties of the signals, while the second one is based on their spectral characteristics. A formal extension of these two models to 2D processes is developed and implemented, and a comparison of both is presented. The proposed algorithms are tested using tomographic brain tumor data. Our simulation experiments offer promising results in the identification of such lesions.

关键词： Fractals Signal analysis Brownian motion Biomedical imaging Mathematical model Wavelet analysis Signal processing Testing Tomography Neoplasms

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An adaptive velocity estimation approach for improved disk drive control performance

An adaptive velocity estimation approach for improved disk d...

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Annual Conference of Industrial Electronics Society

作者： F. Janabi-Sharifi A. Shademan Robotics and Manufacturing Automation Laboratory Department of Mechanical AeroSpace and Industrial Engineering Ryerson University Toronto Canada Signal and Image Processing Group School of Intelligent Systems IPM Niavaran Tehran Iran

For disk servo system design, it is desired to optimize data storage and transfer subject to the constraints imposed by the servomechanism including velocity estimation and control algorithm, disk space, the actuator, and other limiting factors. Therefore, positioning the head with high accuracy, speed, and reliability is of significant importance. Since velocity estimation is essential for many disk servomechanisms, the quality of head positioning will be governed by the accuracy, speed and reliability of the velocity estimation methods employed. In this paper, adaptive windowing techniques for discrete velocity estimation in disk drives are introduced. The methods are compared with conventional techniques such as finite difference method and Kalman filtering using the introduced measures. It is shown that the proposed techniques generate relatively accurate and reliable estimates with reduced time delays and lower amplitude distortions when compared with the previous methods. Finally, it is demonstrated that the proposed techniques improve the control performance of the disk servo systems.

关键词： Programmable control Adaptive control Disk drives Velocity control Servomechanisms Control systems Constraint optimization Design optimization Memory Actuators

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Adaptive velocity estimation for disk drive head positioning

Adaptive velocity estimation for disk drive head positioning

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IEEE/ASME (AIM) International Conference on Advanced intelligent Mechatronics

作者： A. Shademan F. Janabi-Sharifi Signal and Image Processing Group School of Intelligent Systems Institute of Studies in Theoretical Physics and Mathematics Tehran Iran Robotics and Manufacturing Automation Laboratory Department of Mechanical Aerospace and Industrial Engineering Ryerson University Toronto ONT Canada

With the rapid increase of data areal density in disk drives, the need for more accurate position sensing and velocity estimation techniques for the disk drive head actuator emerges. This paper studies the application of velocity estimation methods for disk drive head positioning servo-mechanism with a focus on adaptive windowing velocity estimation. The adaptive windowing technique requires no prior knowledge of measurement noise and shows a better performance compared to conventional finite difference method and Kalman filtering technique. We have compared the performance of adaptive velocity estimation methods under study over a noisy position trajectory in terms of measures for error statistics and undesired shifting. The undesired shifting measure has been developed to reflect the estimation delay and outliers. The simulation results show the superiority of adaptive windowing velocity estimation to conventional methods.

关键词： Disk drives Delay estimation Actuators Noise measurement Finite difference methods Kalman filters Adaptive filters Filtering Position measurement Velocity measurement

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Automatic face region tracking for highly accurate face recognition in unconstrained environments

Automatic face region tracking for highly accurate face reco...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Y.-O. Kim J. Paik Jingu Heo A. Koschan B. Abidi M. Abidi Korea Electronics and Technology Institute Puchon Gyeonggi South Korea Image Processing Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Tennessee Knoxville USA

We present a combined real-time face region tracking and highly accurate face recognition technique for an intelligent surveillance system. High-resolution face images are very important to achieving accurate identification of a human face. Conventional surveillance or security systems, however, usually provide poor image quality because they use only fixed cameras to record scenes passively. We have implemented a real-time surveillance system that tracks a moving face using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction with the PTZ. Color information in the ROI is updated to extract features for optimal tracking and zooming. FaceIt/sup /spl reg//, which is one of the most popular face recognition software packages, is evaluated and then used to recognize the faces from the video signal. Experimentation with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.

关键词： Face recognition Surveillance Real time systems Humans Cameras intelligent systems Security image quality Layout Low pass filters

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A new time series classification approach

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SIGNAL processing 1996年第2期54卷 191-199页

作者： Plataniotis, KN Androutsos, D Venetsanopoulos, AN Lainiotis, DG Department of Electrical and Computer Engineering Digital Signal & Image Processing Laboratory University of Toronto 10 King's College Rd. Toronto Ontario M5S 3G4 Canada Intelligent Systems Technology 3207 S. Hwy. A1A Melbourne Beach FL-32951 USA

A new, robust and computationally attractive approach to the problem of time series classification is discussed in this paper. Both the Bayesian as well as a new adaptive classification scheme for source selection are... 详细信息

关键词： time series classification neural networks logistic function

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Measuring the distance and orientation of a planar surface using nonstructured lighting

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systems AND COMPUTERS IN JAPAN 1996年第8期27卷 83-92页

作者： Tsukiyama, T Member Electrotechnical Laboratory Tsukuba Japan 305 Tosbifumi Tsukiyama:graduated in 1972 from the Biological Engineering Department Osaka University where he also received his Dr. of Eng. degree. He joined Electrotechnical Laboratory Ministry of Tread and Industry (Japan) in 1972. At present he is Senior Researcher at Computer Vision Section Intelligent Systems Division ETL. He was a Visiting Researcher at University of Illinois during 1984–1985. He has been interested in vision system for mobile robots and image processing architectures. He is a member of the Society of Instrumental and Control Engineers Japan Robotics Society of Japan and Information Processing Society of Japan.

This paper proposes a method of 3-dimensional measurement of a planar surface by using two fixed light sources and a TV camera. A set of two images is recorded by the camera switching on each light alternately. The peak of the luminance distribution in each image is detected, and the orientation and distance of the planar surface are calculated. The position of the peak of a luminance distribution can be estimated accurately by using an image processing. The light sources can be conventional apparatus with no particular structure. The method is simple and suitable for a vision system on an indoor mobile robot.

关键词： distance to surface orientation of planar surface point light source luminance distribution ring light

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