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An Efficient Method of License Plate Location Based on Structure Features

An Efficient Method of License Plate Location Based on Struc...

引用

The 2011 International Conference on Business, Economics, and Financial sciences, Management (BEFM 2011)

作者： Fan Ye Mei Xie Image Processing and Information Security Lab School of Electronic EngineeringUniversity of Electronic Science and Technology of China

License plate recognition system is an important part of intelligent transportation system,while the vehicle license plate location is the key of *** this paper,a new method of license plate(LP)positioning is *** this method,firstly,the input image is ***,the texture and color features are used to remove most of *** that,the regions which have the structure and texture that is similar to the license plate are ***,pseudo-region is eliminated and true LP is precisely *** working principle is taking full advantages of plate texture,color characteristic and structure features to choose candidate *** results illustrate that the method is robust and can increase the location accuracy distinctly.

关键词： Vehicle license plate location,texture,color,pseudo-region,structure features

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Homography-based ground area detection for indoor mobile robot using binocular cameras

Homography-based ground area detection for indoor mobile rob...

引用

2011 IEEE 5th International Conference on Robotics, Automation and Mechatronics, RAM 2011

作者： Ke, Peiqi Meng, Cai Li, Jihao Liu, Ying Image Processing Center School of Astronautics Beihang University Beijing 100191 China Social Robotics Lab. Interactive Digital Media Institute National University of Singapore 119613 Singapore Singapore Mechatronics Engineering Department School of Mechanical Engineering Beijing University of Science Technology Beijing 100083 China Industrial Robot and Production Automation Lab. School of Mechanical Engineering University of Science and Technology Beijing Beijing 100083 China

ISBN: (纸本)9781612842509

Drivable area detection is an important issue for mobile robot to work in indoor and outdoor environments with safety and security with respect to itself and environment. In this paper, we propose an approach to detect the ground area for indoor mobile robots with binocular cameras. At first, the ground induced homography between onboard binocular cameras is calibrated. In ground area detection, the right eye image is warped to left eye by the homography and subtracted by the left eye image. From the difference image the rough non-ground regions can be detected. Then the closed contours on the difference image and the left eye image are searched to segment them into regions. These corresponding regions are compared to judge whether they belong to ground plane. The conducted experiments show that the proposed method is valid in detecting ground area. © 2011 IEEE.

关键词： Mobile robots

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3D Diffusion tensor magnetic resonance images denoising based on sparse representation

3D Diffusion tensor magnetic resonance images denoising base...

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2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011

作者： Kong, You-Yong Wang, De-Feng Wang, Tian-Fu Chu, Winnie Cw Ahuja, A.T. Laboratory of Image Science and Technology School of Computer Science and Engineering Southeast University Nanjing 210096 China Department of Imaging and Interventional Radiology Chinese University of Hong Kong Shatin N.T. Hong Kong Shenzhen Key Lab of Biomedical Engineering School of Medicine Shenzhen University Shenzhen Guangdong China

ISBN: (纸本)9781457703065

Diffusion tensor magnetic resonance imaging (DT-MRI) is widely used to characterize white matter health and brain disease. However, the DT-MRI is very sensitive to noise. This paper proposes a sparse representation based denoising method for 3D diffusion weighted images (DWI) in DT-MRI. As consecutive 2D images in DWI volume have similar content and structure, we can process a fixed number of adjacent images from DWI volume simultaneously. The proposed method first learned a dictionary from the selected 2d diffusion weighted images according to the K-SVD learning algorithm. Then the clean images are obtained by gradually approximating the underlying images using the bases selected from the learned dictionary based on sparse representation. At last, the tensor images are estimated from the diffusion weighted images. The experiments on both synthetic and real DT-MRI images show that the proposed method performs better than classical techniques by preserving image contrast and structures. © 2011 IEEE.

关键词： image denoising

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Maximal cliques that satisfy hard constraints with application to deformable object model learning

Maximal cliques that satisfy hard constraints with applicati...

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25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

作者： Wang, Xinggang Bai, Xiang Yang, Xingwei Liu, Wenyu Latecki, Longin Jan Dept. of Electronics and Information Engineering Huazhong Univ. of Science and Technology China Image Analytics Lab. GE Research One Research Circle Niskayuna NY 12309 United States Dept. of Computer and Information Sciences Temple Univ. United States

ISBN: (纸本)9781618395993

We propose a novel inference framework for finding maximal cliques in a weighted graph that satisfy hard constraints. The constraints specify the graph nodes that must belong to the solution as well as mutual exclusions of graph nodes, i.e., sets of nodes that cannot belong to the same solution. The proposed inference is based on a novel particle filter algorithm with state permeations. We apply the inference framework to a challenging problem of learning part-based, deformable object models. Two core problems in the learning framework, matching of image patches and finding salient parts, are formulated as two instances of the problem of finding maximal cliques with hard constraints. Our learning framework yields discriminative part based object models that achieve very good detection rate, and outperform other methods on object classes with large deformation.

关键词： Inference engines

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Enhanced classification of focal hepatic lesions in ultrasound images using novel texture features

Enhanced classification of focal hepatic lesions in ultrasou...

引用

IEEE International Conference on image Processing

作者： Sihyoung Lee In A Jo Kyung Won Kim Jae Young Lee Yong Man Ro Image and Video Systems Lab Korea Advanced Institute of Science and Technology South Korea Department of Radiology Seoul National University South Korea

This paper discusses novel texture features that allow providing enhanced classification accuracy for focal hepatic lesions. The proposed texture features takes advantage of the rotation and scale invariant nature of Gabor wavelets, as well as the gray-level co-occurrence matrix (GLCM) for analyzing the spatial distribution of the pixel intensity in the lesion. To verify the effectiveness of the proposed texture features, experiments were performed with 150 ultrasound images containing 150 focal hepatic lesions, consisting of 50 cysts, 50 hemangiomas, and 50 malignancies. Experimental results show that the proposed texture features allow for an improved classification performance, compared to the use of other features.

关键词： Lesions Feature extraction Ultrasonic imaging image segmentation Support vector machines Kernel Conferences

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Finding protein active sites using approximate sub-graph isomorphism

Finding protein active sites using approximate sub-graph iso...

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Middle East Conference on Biomedical Engineering (MECBME)

作者： Mohammad Ebrahim Abbasi Dezfouli Seyed Shahriar Arab Emad Fatemizadeh Najmeh Hosseynimanesh Electrical Engineering Department BiSIPL (Biomedical Image and Signal Processing Lab) Sharif University of Technology Tehran Iran School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran

Prediction of the amino acids that have a catalytic effect on the enzymes is a major stage in appointing the activity of the enzymes and classification. The biological activity of a protein usually depends on the existence of a small number of amino acids. Recently, many algorithms have been proposed in the literature for finding these amino acids which are complex and time consuming. In this paper, we will introduce a new method for predicting the active sites that will use the spatial coordinates and the type of amino acids that contain the active sites. In order to increase the speed we use an approximate graph isomorphism algorithm. Furthermore, this algorithm allows us to find several active sites for a protein and order them according to a RMSD (Root Mean Square Deviation) number which has several applications in biology.

关键词： Proteins Amino acids Approximation algorithms Protein engineering Classification algorithms Databases

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Segmentation of Brain Tumors in MRI images Using Multi-scale Gradient Vector Flow

Segmentation of Brain Tumors in MRI Images Using Multi-scale...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Anahita Fathi Kazerooni Alireza Ahmadian Nassim Dadashi Serej Hamidreza Saligheh Rad Hooshang Saberi Hossein Yousefi Parastoo Farnia Department of Biomedical Systems & Medical Physics Tehran University of Medical Sciences (TUMS) and Image Guided Surgery Lab Research Center for Science and technology in Medicine (RCSTIM) Department of Biomedical Systems & Medical Physics Tehran University of Medical Sciences and Image Guided Surgery Lab Research Center for Science and technology in Medicine (RCSTIM) Department of Neurosurgery Imam Khomeini Hospital Tehran University of Medical Sciences and Brain and Spinal Injuries Repair Research Center (BASIR)

ISBN: (纸本)9781424441211

The gradient vector flow (GVF) algorithm has been used extensively as an efficient method for medical image segmentation. This algorithm suffers from poor robustness against noise as well as lack of convergence in small scale details and concavities. As a cure to this problem, in this paper the idea of multi scale is applied to the traditional GVF algorithm for segmentation of brain tumors in MRI images. Using this idea, the active contour is evolved with respect to scaled edge maps in a multi scale manner. The edge detection performance of the modified GVF algorithm is further enhanced by applying a threshold-based edge detector to improve the edge map. The Bspline snake is selected for representation of the active contour, due to its ability to capture corners and its local control. The results showed an improvement of 30% in the accuracy of tumor segmentation against traditional GVF and 10% as compared to Bspline GVF in the presence of noise, besides the repeatability of the algorithm in contrast to traditional GVF. The clinical evaluation also proved the accuracy and sensitivity of the proposed method as 92.8% and 95.4%, respectively.

关键词： Brain tumor segmentation Multi scale GVF Traditional GVF B-spline snake

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Homography-based ground area detection for indoor mobile robot using binocular cameras

Homography-based ground area detection for indoor mobile rob...

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Peiqi Ke Cai Meng Jihao Li Ying Liu Image Processing Center School of Astronautics Beihang University Beijing 100191 China Social Robotics Lab Interactive Digital Media Institute National University of Singapore 119613 Singapore Mechatronics Engineering Department School of Mechanical Engineering Beijing University of Science Technology 100083 China Industrial Robot & Production Automation Lab School of Mechanical Engineering University of Science & Technology Beijing 100083 China

关键词： Mobile robots Cameras Conferences Automation image segmentation Robot vision systems

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Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning 11

Maximal Cliques that Satisfy Hard Constraints with Applicati...

引用

Annual Conference on Neural Information Processing Systems

作者： Xinggang Wang XiangBai Xingwei Yang Wenyu Liu Longin Jan Latecki Dept. of Electronics and Information Engineering Huazhong Univ. of Science and Technology China Image Analytics Lab GE Research One Research Circle Niskayuna NY 12309 USA Dept. of Computer and Information Sciences Temple Univ. USA

ISBN: (纸本)9781618395993

关键词： mutual exclusion detection rate (DR) Particle filtering algorithm Learning image patch Ganglia object information model Maximal Frameworks Satisfaction

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Control of a rehabilitation robotic exoskeleton based on intentional reaching direction

Control of a rehabilitation robotic exoskeleton based on int...

引用

21st Annual Symposium on Micro-Nano Mechatronics and Human science, MHS 2010, Micro-Nano GCOE 2010, Bio-Manipulation 2010

作者： Huo, Weiguang Huang, Jian Wang, Yongji Wu, Jun Key Lab of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424479962

An upper limb robotic exoskeleton of three degrees of freedom (DOF) is designed for the patients who survived stroke and the elderly who have not enough strength to move their limbs freely. Particular attention is paid to the realization of a intention-driven robotic control approach, by which the robotic exoskeleton can assist the user moving his/her arm freely to where he/she intends to go. A force sensing system made of multiple force sensing resisters (FSRs) is embedded in the robotic exoskeleton. A static force model of the upper limb in a relaxed state is obtained when the user wears the exoskeleton. A hybrid model is proposed to describe the behavior modes of human upper limb motion. Filtering technology is designed to infer the intended moving direction of upper limb based on the measured force information and the static force model. The motion intention of user's upper limb can be online estimated using the filter and a mode transition detector. Guided by the inferred intention, an admittance control strategy is assumed to control the motors of each DOF. The effectiveness of proposed robotic system and control approaches is evaluated by experiments. ©2010 IEEE.

关键词： Degrees of freedom (mechanics)

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