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检索条件"机构=Vienna University of Technology Pattern Recognition and Image Processing"

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MULTISPECTRAL IMAGING FOR ANALYZING ANCIENT MANUSCRIPTS

MULTISPECTRAL IMAGING FOR ANALYZING ANCIENT MANUSCRIPTS

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European signal processing conference

作者： Martin Lettner Robert Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Vienna University of Technology 1040 Vienna Austria

ISBN: (纸本)9781617388767

In this paper we propose a method for segmenting characters in multispectral images of ancient documents. Due to the low quality of the document images the main idea of our study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov Random Field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. The whole process is parameter free since we calculate the stroke properties and the Gaussian parameters for the imaging model automatically. The study shows the effectiveness of using multispectral data for a computer aided analysis of ancient text documents. We compare the results of the proposed segmentation method to traditional methods based on color images as well as gray level images.

关键词： MULTISPECTRAL Computer aided analysis grayscale images Imaging Spatial Dependency image information color image field simulation

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Medical ultrasound image segmentation Based on improved watershed scheme

Medical ultrasound image segmentation Based on improved wate...

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The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

作者： Wenjie Mao Liang Li Yingxia Fu Peirui Bai Shandong University of Science and technology Institute of Image Processing and Pattern Recognition Shandong University of Science and Technology College of Resource and Environment Engineering Qingda Shandong University of Science and technology Institute of Image Processing and Pattern Recognition

with the characteristics of precision edge and closed contour, watershed segmentation algorithm is used widely in image segmentation. However, over-segmentation always occurs when it is applied to ultrasound images associated with speckle noise. In this paper, an improved watershed segmentation scheme is proposed based on comprehensive consideration of gray scale information, edge information and the relationship between neighboring regions of ultrasound images. A novel criteria deciding the relationship between neighboring regions was defined, and edge information was also added to the merging guidelines. Similar region merging was then applied to the initial segmentation results. The proposed scheme was tested using representative ultrasound image. The experimental results show that the proposed scheme can produce accurate contours and overcome the over-segmentation phenomenon availably.

关键词： Watershed algorithm Medical ultrasound image Similar region merging Gray information Edge information Relationship between neighboring regions

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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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A point-pattern matching method based on maximal subset of one-to-one mapping

A point-pattern matching method based on maximal subset of o...

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MIPPR 2009 - pattern recognition and Computer Vision: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Hu, Jing Zhang, Tian-Xu Institute for Pattern Recognition and AI Hua Zhong University of Science and Technology Wuhan 430074 China Key Lab. of Education Ministry for Image Processing and Intelligent Control Hua Zhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper presents a new affine registration approach for planar point pattern matching. A process of parameter space clustering is implemented to confirm a one-to-one mapping between the maximal subsets of feature point sets in images. For a best performance, a coarse parameter space and a fine parameter space are used for vectors comparison. Experiments show that the method can produce positive results from a small number of feature points and intensive noise. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Affine transforms

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The Algorithm for Matching 2D Contours Based on V-System

The Algorithm for Matching 2D Contours Based on V-System

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Chinese Conference on pattern recognition (CCPR)

作者： Caixia Zhang Zhihua Miao Fengmei Sun Institute of Image Processing and Pattern Recognition North-China University of Technology Beijing China

Curve matching is one of key issues in computer vision, image analysis and pattern recognition. Based on discrete V-transform, the distance is calculated between curves using the descriptor of V-system to find the matching curves, and then the matching parameters are evaluated in this article. The new approach can find efficiently the rough location of a short extracted image curve in a long reference curve. Different from the existing approaches, it needn't to extract feature points. Extensive tests show that it is efficient.

关键词： pattern matching pattern recognition image processing Computer vision image analysis Feature extraction Testing

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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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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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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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