检索结果-内蒙古大学图书馆

第三十三届中国控制会议

作者： YANG Yawen ZHANG Peng Peng QIAO Yu YANG Jie WANG Sheng Zheng The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong University Merchant Marine College Shanghai Maritime University

ISBN: (纸本)9781479947249

Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the process of matching a *** this method,one set of points are thought to be sampled from a Gaussian Mixture Model(GMM),which is centered by the other set of ***,CPD is sensitive to outliers and noises,especially when the noise ratio increased or the number of outliers gets much *** deal with this problem,we introduce shape context into the step of searching for matching points and then improve the form of prior probabilities of GMM in this *** main idea of our method is that if the most points in a data set are likely to be matched to a particular centroid,this Gaussian component should be have a more influence to ***,we set prior probability of GMM with the similarity between GMM components and the data *** the computation of similarity is based on shape *** experiments on 2D and 3D images show that when noise ratio is low,our method performs as well as CPD does,but as the ratio increased,our method is more robust and satisfactory than CPD.

关键词： CPD,Shape context,image registration,Point matching

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Posterior distribution learning (PDL): A novel supervised learning framework

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8834卷 86-94页

作者： Tu, Enmei Yang, Jie Jia, Zhenghong Kasabov, Nicola Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China School of Information Science and Engineering Xinjiang University Urumqi830046 China The Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

In order to obtain a robust supervised model with good generalization ability, traditional supervised learning method has to be trained with sufficient well labeled and uniformly distributed samples. However, in many real applications, the cost of labeled samples is generally very expensive. How to make use of ample easily available unlabeled samples to remedy the insufficiency of labeled samples to train a supervised model is of great interest and practical significance. In this paper we propose a new supervised learning framework, Posterior Distribution Learning (PDL), which could train a robust supervised model with very a few labeled samples by including those unlabeled samples into training stage. Experimental results on both synthetic and real world data sets are presented to demonstrate the effectiveness of the proposed framework. © Springer International Publishing Switzerland 2014.

关键词： Supervised learning

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Detection level of mango based on neural network and digital image

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Journal of Chemical and Pharmaceutical Research 2014年第2期6卷 129-132页

作者： Li, Xiaoling Yuan, Jimin School of Computer Science and Technology of Chengdu University China University Key Laboratory of Pattern Recognition and Intelligent Information Processing China Department Computer Engineering of Chengdu Aeronautic Vocational and Technical College China

In view of the draw backs of mango grade identification in China, which still relies on photoelectric sorting and manual separation, this paper presents a processing method on the basis of the technology of computer vision and digital image. Utilizing image processing technology, the researcher calculated the length of the long-short-axis, marked the location of it and calculated the 7 parameters, chroma, length, width and etc.,4 of which are chosen as the key characteristics of the BP input of network to build a network and identify the level of mango through analysis of the external characteristics of mango. The method is based on traditional characteristics detection, using boundary tracking algorithm and the length of the new long-short-axis detection algorithm. The result of experiment indicates that the calculating method and judging of the level of mango are precise and accurate, with an average recognition rate of 92%. Therefore, the method has a great practical value, which can be applied to other agricultural products classification.

关键词： Fruits

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Low energy-consuming cluster-based algorithm to enforce integrity and preserve privacy in data aggregation

Low energy-consuming cluster-based algorithm to enforce inte...

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13th International Symposium on Distributed Computing and Applications to Business,engineering & Science（DCABES 2014）

作者： Zhengwei Guo Xiaojiao Ding College of Computer & Information Engineering Institute of Image Processing & Pattern Recognition Henan University

This paper proposes a low energy-consuming cluster-based algorithm to protect data integrity and privacy named ILCCPDA, which can dynamically elect cluster head by LEACH clustering protocol and take the simple cluster fusion approach to reduce the data transmission, thus reducing energy consumption. ILCCPDA can detect data integrity by adding homomorphic message authentication code and take the random key distribution mechanism for data encryption. It can solve the problem of the integrity, privacy and energy consumption in the wireless transmission of sensor data.

关键词： wireless sensor networks(WSN) data aggregation privacy protection

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Unsupervised detection of different SAR images based on improved NSCT domain image fusion algorithm

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Guangdianzi Jiguang/Journal of Optoelectronics Laser 2015年第10期26卷 2023-2030页

作者： Zhang, Yi-Chen Jia, Zhen-Hong Qin, Xi-Zhong Yang, Jie Kasabov, Nikola College of Information Science and Engineering Xinjiang University Urumqi China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Aukland New Zealand

In order to reduce the total errors and obtain a better result in change detection with different SAR images, an unsupervised change detection algorithm is proposed in this paper. The technique is based on nonsubsampled contourlet transform (NSCT) domain with an improved fusion algorithm and fuzzy local information C-means clustering (FLICMC). First of all, mean-ratio operation and log-ratio operation are adopted to obtain the difference image, by using two images acquired in the same geographical area at different moments. Secondly, the two difference images are transformed into NSCT domain. The low frequency coefficients of two images of difference images respectively are fused by the rule of the maximum gradient quadratic sum;the high frequency coefficients of two images of difference images respectively are fused by the rule of the weighted fusion. And the final difference image can be got by using NSCT inverse transform. Finally, on the basis of FLICMC algorithm, the final difference image is divided into change area and unchanged area. According to the research between the real remote sensing data set and the simulated remote sensing data set, the experimental results show that the proposed algorithm can effectively suppress speckle noise impact on the detection results, and is not limited by the statistical distribution of change class and unchanged class. It has great applicability and doesn't require prior knowledge. So the proposed algorithm can get better detection effect. Compared with DWT2-FLICMC and MRF-FCMC, the proposed algorithm can obtain higher detection accuracy and shorter running time. ©, 2015, Board of Optronics Lasers. All right reserved.

关键词： Synthetic aperture radar

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on image processing, computer Vision, and pattern recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Low energy-consuming cluster-based algorithm to enforce integrity and preserve privacy in data aggregation

Low energy-consuming cluster-based algorithm to enforce inte...

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The 13th International Symposium on Distributed Computing and Applications to Business,engineering and Science(DCABES 2014)(第十三届分布式计算及其应用国际学术研讨会)

作者： Zhengwei Guo Xiaojiao Ding College of Computer & Information Engineering Institute of Image Processing & Pattern Recognition Henan University KaifengChina

ISBN: (纸本)9781479941681

This paper proposes a low energy-consuming cluster-based algorithm to protect data integrity and privacy named ILCCPDA,which can dynamically elect cluster head by LEACH clustering protocol and take the simple cluster fusion approach to reduce the data transmission,thus reducing energy *** can detect data integrity by adding homomorphic message authentication code and take the random key distribution mechanism for data *** can solve the problem of the integrity,privacy and energy consumption in the wireless transmission of sensor data.

关键词： wireless sensor networks(WSN) data aggregation privacy protection

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Mean Shift Based Feature Points Selection Algorithm of DSA images

Mean Shift Based Feature Points Selection Algorithm of DSA I...

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第三届健康信息学国际学术会议（HIS 2014）

作者： Fan Zhang Congcong Li Shan Kong Shuyue Liu Yanbin Cui School of Computer and Information Engineering Henan University Institute of Image Processing and Pattern Recognition Henan University

In Digital Subtraction Angiography(DSA) image registration algorithm,the precision of the control points as well as their number and the distribution in image determine the accuracy of geometric correction and registrationControl points usually adopt the grid points;however,a more effective method is to extract control points adaptively according to the image featureIn this paper,a control point's selection algorithm of DSA images is proposed based on adaptive multi-Scale vascular enhancement,error diffusion and means shift algorithmsExperimental results show that the proposed algorithm can adaptively put the control points to blood vessels and other key image characteristics,and can optimize the number of control points according to practical needs,which will ensure the accuracy of DSA image registration.

关键词： Digital subtraction angiography,Error diffusion,Mean shift

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A novel level set method for remote sensing image based on K-means

A novel level set method for remote sensing image based on K...

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2014 International Conference on Applied Mechanics, Mechatronics and Intelligent System, AMMIS 2014

作者： Xu, Er Jing Jia, Zhen Hong Wang, Lie Jun Hu, Ying Jie Yang, Jie College of Information science and engineering Xinjiang University Urumchi 830046 China Knowledge Engineering and Research Discovery Institute Auckland University of Technology Auckland New Zealand The Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783038351757

Due to the characteristic of remote sensing image, we propose a novel method based on K-means algorithm also with the improved multi-phrase level set model. Comparing with the classical multi-phase C-V model, the improved model considers the region area information, gradient information and edge detection. Proper use of gradient information can overcome the inaccurate edge localization defects in image segmentation. The edge detection is used for keeping the boundary information better in the evolution process. For the reason of picking up the contour's convergent speed and enable the avoidance of trap. Four stages are constructed. Firstly, a median filtering is applied to smooth the original image and reduce parts of noise. Secondly, the usage of K-means algorithm gains more obvious differences of characteristics. Next, the reconstruction of gradient is obtained by using Sobel operator. Finally, segmentation result is achieved by using an improved method of multi-phase level set image segmentation. Experimental results show that the proposed approach has advantages in rapid and efficient application of remote sensing image segmentation. © (2014) Trans Tech Publications, Switzerland.

关键词： image segmentation

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Color-Coded Imaging with Adaptive Multiscale Spatial Filtering

Color-Coded Imaging with Adaptive Multiscale Spatial Filteri...

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第三届健康信息学国际学术会议（HIS 2014）

作者： Xinhong Zhang Xiaopan Chen Congcong Li Fan Zhang Software School Henan University School of Computer and Information Engineering Henan University Institute of Image Processing and Pattern Recognition Henan University

Digital subtraction angiography has become one of the most important approaches to artery disease diagnosis and treatmentDoctors implement diagnose and treatment by subjective analysis of the DSA series,and the results are always dependent on doctors' experienceThe application of color-coded imaging technology makes it convenient to identify images and provides additional physiology information auxiliary diagnosis and treatmentBefore implementing color-coded imaging technology on DSA series,we preprocess the images with several mutiscale spatial filters to remove noises and enhance vessel structures to make the results readable and clear.

关键词： Color-coded imaging,Digital Subtraction Angiography,Multiscale Spatial filtering

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