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检索条件"机构=Key Laboratory of Image Processing and Pattern Recognition"

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A flower algorithm for autonomous star pattern recognition

A flower algorithm for autonomous star pattern recognition

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作者： Gong, Jiaqi Ma, Jie Tian, Jinwen State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781563479694

An autonomous star pattern recognition algorithm is proposed herein that is effectively stable against the higher level noise than other algorithms. In simulations using an 8×8 degree field of view (FOV), the algorithm identifies the correct section of sky on 99.5% of the sensor orientations where spatial accuracy of the imaged star is 2 pixels (0.03 degree) in standard deviation and the apparent brightness deviate by 0.5 units' stellar magnitude. The achievable performance comes from the generation of the Flower-code pattern, which includes angular distances and circular angles as the characteristics of the pivot star. The angular distances are used for initial lookup table match. Moreover, the circular angles are adopted for the cyclic dynamic match between the sensor pattern and the pattern candidates from the initial match. And also, the performance is demonstrated via a comparison study on two published algorithms. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Table lookup

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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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Path planning for UAV based on quantum-behaved particle swarm optimization

Path planning for UAV based on quantum-behaved particle swar...

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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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A novel algorithm for small dim target detection in distorted infrared image sequence

A novel algorithm for small dim target detection in distorte...

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MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Qu, Xiaolei Zuo, Zhengrong Li, Xiafeng Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multispectral Information Processing Technologies Huazhong University of Science and Technology Wuhan Hubei 430074 China

ISBN: (纸本)9780819478061

A novel algorithm is proposed in this paper to detect dim moving point target with several pixels size in infrared image sequence, taken by line scan camera in high speed moving platform, with heavy background clutter and distortion. In the algorithm, the regional information of candidate points, which are extracted from the images after background suppression by spatial filter, is employed to track candidate points. After tracking candidate points, the velocity of every candidate points can be calculated easily, and false candidate points which are extracted from clutter background, can be find out by velocity classification and removed. Then, Double Hough Transform is applied on associating the remnant candidate points in multi-frame sequence to detect the target. The algorithm can get a high detection probability and reduce false alarm rate dramatically. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Hough transforms

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Global systolic array for fast computation of 3-D moment invariants

Global systolic array for fast computation of 3-D moment inv...

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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： Liu, J.G. Chen, Shaobo Wang, Hai State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology WuHan HuBei 430074 China

ISBN: (纸本)9780819478085

The 3-D moment invariants are introduced to solve the problem of recognition of 3-D objects independent of size, position, and orientation. In this paper, based on our previous systolic array for fast computation of 3-D moment, we propose a new global systolic array for fast computation of 3-D moment invariants. The systolic sarray mostly consists of adders with area complexity O(n) and are highly regular and structurally very simple, resulting in simple hardware implementation. The method is suitable for both binary images and gray level images and is also suitable for image sequence moments. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Systolic arrays

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A fusion method for multispectral and panchromatic images based on HSI and Contourlet transformation

A fusion method for multispectral and panchromatic images ba...

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International Workshop on image Analysis for Multimedia Interactive Services, WIAMIS

作者： Mengxin Song Xinyu Chen Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Fusion of multispectral and panchromatic remote sensing images is a procedure to obtain spatial resolution and quality of the panchromatic image as well as preserving spectral information of the multispectral image. In this paper, we present a new fusion method based on HSI (Hue-Saturation-Intensity) and Contourlet transform. First, we convert the multispectral image from the RGB color space into the HSI color space. Then, by applying Contourlet transform to the panchromatic image and the I component of the multispectral image, we utilize an improved fusion rule based on PCA for the low-frequency sub-images, and engage the maximum fusion rule for the high-frequency sub-images. Finally, a fusion image is obtained by the inverse HSI transform. The experimental results show that the proposed fusion method not only enhances the spatial resolution of the fusion image, but also preserves the spectral information of the original multispectral image.

关键词： Spatial resolution Principal component analysis Multispectral imaging Wavelet transforms Remote sensing Frequency Discrete wavelet transforms image resolution Fuses Fourier transforms

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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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Contour-based multisensor image registration using gradient vector features

Contour-based multisensor image registration using gradient ...

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MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Ming, Delie Wang, Mi Gao, Pengfei State Key Laboratory for Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

ISBN: (纸本)9780819478061

Multi-sensor image registration plays an important role in the automatic targets acquirement (ATA). In this paper, two kinds of new multi-sensor image registration methods based on contour feature are put forward. One is gradient vector correlation coefficient method which is based on contour characteristics of the image, the other is called relative gradient difference method which is in fact a measurement of differences between out-contour area and inner area of the target. Lots of experimental data composed of satellite images and real-time infrared images are used to verify the above two algorithms, and the results show that the two proposed methods can have good performances for both day and night infrared images. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image registration

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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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