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MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Fu, Yangguang Ding, Mingyue Zhou, Chengping Cai, Chao Sun, Yangguang Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

Based on quantum-behaved particle swarm optimization (QPSO), a novel path planner for unmanned aerial vehicle (UAV) is employed to generate a safe and flyable path. The standard particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are presented and compared through a UAV path planning application. Every particle in swarm represents a potential path in search space. For the purpose of pruning the search space, constraints are incorporated into the pre-specified cost function, which is used to evaluate whether a particle is good or not. As the system iterated, each particle is pulled toward its local attractor, which is located between the personal best position (pbest) and the global best position (gbest) based on the interaction of particles' individual searches and group's public search. For the sake of simplicity, we only consider planning the projection of path on the plane and assume threats are static instead of moving. Simulation results demonstrated the effectiveness and feasibility of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Fast on-ship route planning using improved sparse A-star algorithm for UAVs

Fast on-ship route planning using improved sparse A-star alg...

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MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Yang, Xin Ding, Mingyue Zhou, Chengping Cai, Chao Yu, Qi Shao, Shuai Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

This paper presented improved Sparse A-Star Search (SAS) algorithm to pursue a fast route planner for Unmanned Aerial Vehicles (UAVs) on-ship applications. Our approach can quickly produce 3-D trajectories composed by a set of successive navigation points from certain known initial locations to predetermined target locations. The result routes are not only ensuring collision avoidance with the environmental obstacles, but also satisfying specific routes constraints and objectives. The experiment results demonstrated the feasibility of the method, which makes our route planner be more useful in real systems. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Ships

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Needle segmentation in 3D ultrasound images based on phase-grouping

Needle segmentation in 3D ultrasound images based on phase-g...

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MIPPR 2009 - Medical Imaging, Parallel processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Zhao, Siying Qiu, Wu Ming, Yuchi Ding, Mingyue Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Hubei 10086 China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China School of Life Science and Technology Huazhong University of Science and Technology Hubei 10086 China

ISBN: (纸本)9780819478085

Three Dimensional (3D) ultrasound images can provide spatial information to help doctors locate the needle position precisely in ultrasound-guided surgery. In this paper, we present a method called "3D Phase-grouping" to segment the needle inside the patient. The method is an extension from 2D phase-grouping to the 3D case via a new mathematic model-the outer products of adjacent orientation vectors. Firstly, the voxels with the same outer products of the gradient orientation vectors of the adjacent points are divided into Line Support Regions (LSR). Then, the needle is extracted with the 3D Least-Squares line fitting method in the maximal LSR. Synthetic and 3D ultrasound phantom data were tested. The segmentation results were evaluated by the angular deviation, position deviation and computational time. Compared with the 3D Hough transform, 3D Phase-Grouping is more accurate and faster without using pre-information. The computational complexity and robustness of the algorithm remain to be our future research topics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Needles

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Incremental learning in nonstationary environments with controlled forgetting

Incremental learning in nonstationary environments with cont...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ryan Elwell Robi Polikar Signal Processing and Pattern Recognition Laboratory Electrical and Computer Engineering Department Rowan University Glassboro NJ USA

We have recently introduced an incremental learning algorithm, called Learn ++ .NSE, designed for Non-Stationary Environments (concept drift), where the underlying data distribution changes over time. With each dataset drawn from a new environment, Learn ++ .NSE generates a new classifier to form an ensemble of classifiers. The ensemble members are combined through a dynamically weighted majority voting, where voting weights are determined based on classifiers' age-adjusted accuracy on current and past environments. Unlike other ensemble-based concept drift algorithms, Learn ++ .NSE does not discard prior classifiers, allowing potentially cyclical environments to be learned more effectively. While Learn ++ .NSE has been shown to work well on a variety of concept drift problems, a potential shortcoming of this approach is the cumulative nature of the ensemble size. In this contribution, we expand our analysis of the algorithm to include various ensemble pruning methods to introduce controlled forgetting. Error or age-based pruning methods have been integrated into the algorithm to prevent potential out-voting from irrelevant classifiers or simply to save memory over an extended period of time. Here, we analyze the tradeoff between these precautions and the desire to handle recurring contexts (cyclical data). Comparisons are made using several scenarios that introduce various types of drift.

关键词： Neutron spin echo Algorithm design and analysis Voting

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Path Integral Based Contour Extraction Method Using Multilevel Metropolis Sampling

Path Integral Based Contour Extraction Method Using Multilev...

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7th International Conference on Photonics and Imaging in Biology and Medicine

作者： Yangguang, Sun Tian, Lan Xiaowei, Fu Mingyue, Ding Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819475398

In this paper we proposed a novel path integral method using multilevel Metropolis sampling to extract the contours of interested objects of medical images, which is a quantum statistical approach inspired by the essential characteristics of quantum. The implemented multilevel Metropolis sampling is a fast approach to the sampling problem and can be used to sample any distribution function and calculate all actions for the movements of quantum particle towards the position with high probability density likely to be accepted. Comparing with traditional deformable models based on classical mechanics which are sensitive to the initialization of contour and difficult to adapt topology changes of the contour, our work has the capability to break through the limitations of deformable models and makes the boundary extraction in high noise and low contrast of medical images possible. Experiments were performed with synthetic and medical images and the feasibility and potential of our method was demonstrated. © 2009 SPIE.

关键词： Distribution functions

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A statistical approach to contour extraction based on quantum mechanics

A statistical approach to contour extraction based on quantu...

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Medical Imaging 2009 - Image processing

作者： Sun, Yangguang Lan, Tian Fu, Xiaowei Ding, Mingyue Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819475107

Contour extraction is a key issue in many medical applications. A novel statistical approach based on quantum mechanics to extract contour of the interested object of medical images was proposed in this paper. The natures of quantum statistical concepts such as the quantum discontinuity and the wave function correspond to the discrete and gray possibility of an image respectively. Contour extraction will be performed by the quantum particle movement, where the particle will be moved forward to the position with high probability density edges in image potential field. Experimental results with medical images demonstrated that the proposed approach has the capability to extract contours with arbitrary initialization and handle topology changes as well as both the inner and outer contours by a single initialization. Keywords: Statistical approach, contour extraction, path integral, quantum mechanics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Medical applications

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Skeleton-based fast path planning for UAV

Skeleton-based fast path planning for UAV

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Liu, Xin Zhou, Chengping Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

A new path planning method for UAV in static workspace is presented. The method can find a nearly optimal path in short time which satisfies the UAV kinematic constraints. The method makes use of the skeletons to construct the graph of the planning space considering the configuration of the obstacles and utilizes the graph to find a shortest collision-free path, and a novel technique is utilized to convert the free path into a feasible path. The method can be applied to different applications and easy to be implemented. Experimental results showed that the path planning can be done in a fraction of second on a contemporary workstation (2-3 seconds) under the condition of satisfying the kinematic constraints. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Analysis of second order motion

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Moshi Shibie yu Rengong Zhineng/pattern recognition and Artificial Intelligence 2009年第3期22卷 344-348页

作者： Sun, Bin Sang, Nong Li, Zheng Zheng, Qing-Qing State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute of Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Technol. Wuhan 430074 China

The study of the second order motion in biological vision is a new source of inspiration for algorithms and research directions in computer vision. In this paper, the second order motion can be divided into three typical group according to the modulation types: spatial modulate motion, temporal modulate motion and spatio-temporal modulate motion. Experiments are conducted on the first order motion perception based on correlation model and the second order motion perception by correlation model preceded with a nonlinear process called texture grabber. The computational results are consistent with the previous suggestion that the second order motions are processed by nonlinear system.

关键词： Modulation

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Feature Sharing Applied to Palmprint Identification

Feature Sharing Applied to Palmprint Identification

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International Conference on Image and Graphics (ICIG)

作者： Ping Zheng Nong Sang State Key Laboratory of Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769552378;9780769538839

Palmprint identification is the means of recognizing an individual from the database using his or her palmprint features. This paper presents a palmprint recognition method by finding common features that can be shared across the classes (different persons), which is a welcome contrast to the existing approaches. At present almost all research is on low resolution images for civil and commercial applications, hence we trained classifiers working in similar feature spaces of the low dimensionality such as texture. In enrollment stage, we randomly select a certain number of samples each class as the training samples. After being preprocessed, the improved SIFT (Scale Invariant Feature Transformation) feature with SAX (Symbolic Aggregate approximation) representation is extracted from the image. The ECOC (Error Correct Output Code) matrix is obtained by layer joint boosting to select the best shared models and their shared features correspondingly. The sum of the weak classifiers which are constructed in each round of boosting turns into the strong classifier. In identification stage, query sample after being extracted features can be directly identified. The experimental results illustrate the effectiveness of the proposed approach.

关键词： Spatial databases Biometrics Boosting Fingerprint recognition Iris pattern recognition Image recognition Feature extraction Graphics Laboratories

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Using Phase and Directional Line Features for Efficient Palmprint Authentication

Using Phase and Directional Line Features for Efficient Palm...

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Congress on Image and Signal processing, CISP

In palmprint recognition, researchers can extract ridges, singular points and minutia points as features from high resolution images while in low resolution images they generally extract principal lines, wrinkles and texture. And now almost all research concentrates on low resolution images for civil and commercial applications. This is also the focus of this paper. In this paper, a new method based on 2D hybrid Log-Gabor filter, D-S evidence theory and ANOVA (Analysis Of Variance) method is proposed for feature extraction. In palmprint images, 2D hybrid Log-Gabor filter is constructed by a number of weighted 2D Log-Gabor filters with different orientations to extract texture mixed-phase feature. And the integration of ANOVA method and D-S evidence theory is then employed for detecting directional line feature by dealing with the uncertain weak edges and the difficulty in threshold selection from multi-images. Finally, a decision based on the measurement of a modified Hamming distance is obtained. Experiments on the Polyu-Online-Palmprint Database show competitive performance.

关键词： Authentication Image resolution Filters Analysis of variance Feature extraction Image edge detection Image recognition Focusing Filtering theory Computer vision

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