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2010 3rd International Congress on image and Signal processing, CISP 2010

作者： Zhang, Weizheng Jiang, Tao Han, Mingqin Image Processing Department Information and Electrical College Shandong University of Science and Technology Qingdao China Remote Sensing Department Geometrics College Shandong University of Science and Technology Qingdao China Key Laboratory of Surveying and Mapping Technology on Island and Reed State Bureau of Surveying and Mapping Qingdao China

ISBN: (纸本)9781424465149

In recent years, with CCD (or CMOS) image sensor as the core components, digital cameras turns into a new generation cameras. Compared with ordinary cameras, digital cameras have a distinct advantage: achieving digital information collection, image processing conveniently, and have been widely used in many fields presently. However, when people using ordinary digital camera doing research, few consider the error of the target image caused by digital camera distortion, digital camera is the important equipment to obtain digital image data, and its camera distortion should attract users attention. To ensure the quality of its results to meet the precision of the measurement tasks, the calibration of each parameter will be an important task. Commonly used camera calibration method including: spatial resection, direct linear transformation, analytical plumb line and self calibration. In this paper we use space resection, obtain calibration images through the establishment of mathematical model calibration, locate the accurate position of pixels and obtain accurate calibration parameters. Getting conclusion by authentication example, provide basic guarantees for the follow-up of Digital close-range photogrammetry and 3D modeling. ©2010 IEEE.

关键词： Digital cameras

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Landuse information extraction in Qingdao based on decision tree classification

Landuse information extraction in Qingdao based on decision ...

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Congress on image and Signal processing, CISP

作者： Han, Mingqin Jiang, Tao Zhang, Weizheng Dong, Shouyin Lu, Wenhu Remote Sensing Department Geometrics College Shandong University of Science and Technology Qingdao China Key Laboratory of Surveying and Mapping Technology on Island and Reed State Bureau of Surveying and Mapping Qingdao China Image Processing Department Information and Electrical College Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9781424465149

The paper first describes the method of decision tree classification and characteristics of domestic and foreign research and elaborated on the basic principles of decision tree classifier and decision tree classifier structure the conditions to be met. On this basis, we extract information from Landsat-ETM+ image in September 16, *** we draw the spectral reflectance curve of the samples from the image, and establish the initial decision tree model. After that, we adjust the initial decision tree model to a satisfactory result. At last;we compared the result of decision tree classification with the result of traditional classification. Studies show that the total accuracy of decision tree method increases by 12.96% and Kappa coefficient by 14.63%. ©2010 IEEE.

关键词： Decision trees

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Quantum-inspired immune clonal clustering algorithm based on watershed

Quantum-inspired immune clonal clustering algorithm based on...

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Congress on Evolutionary Computation

作者： Yangyang Li Nana Wu Jingjing Ma Licheng Jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing and State Key Laboratory of Integrated Services Network Xidian University Xi'an China

Based on the concepts and principles of quantum computing, a novel clustering algorithm, called a quantum-inspired immune clonal clustering algorithm based on watershed (QICW), is proposed to deal with the problem of image segmentation. In QICW, antibody is proliferated and divided into a set of subpopulation groups. Antibodies in a subpopulation group are represented by multi-state gene quantum bits. In the antibody's updating, the quantum mutation operator is applied to accelerate convergence. The quantum recombination realizes the information communication between the subpopulation groups so as to avoid premature convergences. In this paper, the segmentation problem is viewed as a combinatorial optimization problem, the original image is partitioned into small blocks by watershed algorithm, and the quantum-inspired immune clonal algorithm is used to search the optimal clustering centre, and make the sequence of maximum affinity function as clustering result, and finally obtain the segmentation result. Experimental results show that the proposed method is effective for texture image and SAR image segmentation, compared with the genetic clustering algorithm based on watershed (W-GAC), and the k-means algorithm based on watershed (W-KM).

关键词： Clustering algorithms image segmentation Error analysis Radiative recombination Feature extraction Wavelet transforms Partitioning algorithms

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Algorithm of Partition based Network Boosting for imbalanced data classification

Algorithm of Partition based Network Boosting for imbalanced...

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International Joint Conference on Neural Networks (IJCNN)

作者： Gou Shuiping Yang Hui Jiao Licheng Zhuang Xiong Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China and Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

Network Boosting (NB) is an ensemble learning method which combines weak learners together based on a network and can learn the target hypothesis asymptotically. NB has higher generalization ability compared to Bagging and AdaBoost. But, when datasets are class-imbalanced, the performance of NB will decrease quickly. In order to solve this problem, we present a Partition based Network Boosting method (PNB) to classify imbalanced data. For PNB method, every classifier node of the classifier network is provided with the same number of training data which are all of same weights. The classifier in the network is built by the balanced training set sampled from the training data according to the weights record of the training data it holds. And then, the weights of the instances of every node classifier are updated based on the classification results of self-node and its neighbor nodes. The classifier network is trained repeatedly in such a way. Weight factor of hypothesis in the training progress is introduced to improve the performance. The final classification is formed by all the hypotheses of the classifier network learned during the training progress so that the label of new instances can be decided by the weight voting. The experimental results on UCI data and imbalanced biomedical data show that the PNB algorithm has better AUC and recall performance compared with NB learning machine.

关键词： Laboratories Impedance matching Breast Boosting Liver

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Electrode Localization in 3D Ultrasound images Using 3D Phase Grouping and Randomized Hough Transform

Electrode Localization in 3D Ultrasound Images Using 3D Phas...

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International Conference on Genetic and Evolutionary Computing (ICGEC)

作者： Wu Qiu Mingyue Ding Ming Yuchi School of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan China

A method to locate the axis of radio frequency ablation electrode(RFAE) in 3D Ultrasound(US) image is presented based on 3D phase-grouping in this paper. Firstly, all voxels in 3D US images are categorized into different groups which are called Line Support Region(LSR) according to the outer products of adjacent orientation vectors. And then, the RFAE axis is extracted with 3D Randomized Hough transform in the maximal LSR, instead of least squares fitting method, Finally, the endpoint of the RFAE axis is determined by searching along the axis with the probability distribution of voxels. The proposed method was tested in synthetic and 3D US agar phantom datas, the results are promising.

关键词： Three dimensional displays Instruments Ultrasonic imaging Needles image segmentation Transforms Feature extraction

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The Impact of Parsing Accuracy on Syntax-based SMT

The Impact of Parsing Accuracy on Syntax-based SMT

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The 6th International Conference on Natural Language processing and Knowledge Engineering(第六届IEEE自然语言处理与知识工程国际会议 NLP-KE 2010)

作者： Hao ZHANG Huizhen WANG Tong XIAO Jingbo ZHU Key Laboratory of Medical Image Computing (Northeastern University) Ministry of Education Natural Language Processing Laboratory，Northeastern University Shenyang Liaoning P.R.China 110819

ISBN: (纸本)9781424468973

In statistical machine translation (SMT), syntax-based models generally rely on the syntactic information provided by syntactic parsers in source language, target language or both of them. However, whether or how parsers impact the performance of syntax-based systems is still an open issue in the MT field. In this paper, we make an attempt to explore answers to this issue, and empirically investigate the impact of parsing accuracy on MT performance in a state-of-the-art syntax-based system. Our study shows that syntax-based system is not very sensitive to the parsing accuracy of parsers used in building MT systems.

关键词： machine translation syntax-based statistical machine translation (SMT) syntactic parser

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Upper limb rehabilitation robot integrated with motion intention recognition and virtual reality environment

Upper limb rehabilitation robot integrated with motion inten...

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作者： Wu, Jun Huan, Jian Wang, Yongji Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9787894631046

Robotic-assisted therapy is of benefit to the recovery of upper limb motor function for the patients survived stoke. Whereas, there are few emphases on the patients' motion intention during the rehabilitation process. The goal of this study is to combine the control strategies based on patients' motion intention with an upper limb rehabilitation robot to improve the recovery for the patients. In this paper, we propose an integrated robot-assist rehabilitation system, in which a 3 degree-of-freedom (DOF) exoskeletal rehabilitation robot, an EMG-based intention recognition module and a VR game environment are seamlessly combined. According toharacteristics of EMG signals, the wavelet package analysis approach is applied to extract the features of EMG. The node energy is used to construct the feature vector instead of the original coefficients of wavelet package decomposition to resolve the time-invariance problem. Then feature projection results in the singularity problem of with-in scatter matrix during the feature dimension reduction. To overcome the disadvantage of the with-in scatter matrix, this paper uses a recursive algorithm which is proposed in our previous work. The reduced feature vector is recognized by a neural network classifier and the output of the classifier is used for the control inputs. Preliminary experiments are also performed to implement the control of the rehabilitation robotic system by using the proposed EMG reorganization method, together with a dart game realized in the virtual reality environment. Experimental results show that the performance of motion intention recognition is satisfactory and the entire integrated system is feasible.

关键词： Virtual reality

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Symport/antiport P systems with look-ahead mode

Symport/antiport P systems with look-ahead mode

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Yun Jiang Shuo Wang Jinbang Xu Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei China

The look-ahead is a forbidding condition formalized by a set of forbidden rules that are checked after all assignment of objects to rules are done. The look-ahead mode can decrease the inherent non-determinism of P systems and helps to the practical implementation of P systems on computers. In this work, the computational power of P systems with symport/antiport rules working in the look-ahead mode are investigated. communication P systems with 3 membranes and the weight of symport and antiport rules being 2 and 1, respectively, working in the look-ahead mode, can recognize any recursively enumerable languages; a characterization of context-sensitive languages is obtained by communication P systems with 2 membranes working in the look-ahead mode.

关键词： Biomembranes Variable speed drives

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Study of high-resolution range profile for monostatic MIMO radar based on SIAR

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Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics 2010年第4期32卷 734-739+763页

作者： Zhao, Guang-Hui Chen, Bai-Xiao Gao, Zhao-Zhao Intelligent Perception and Image Understanding Key Lab of Ministry of Education of China Xidian Univ. Xi'an 710071 China National Key Lab for Radar Signal Processing Xidian Univ. Xi'an 710071 China National Information Control Laboratory Chengdu 610036 China

Conventional pulse compression use a periodical echo of single receive antenna, which is modulated by a certain carrier-frequency, in other words, single spectrum is exploited. But for MIMO radar, as the multi-carrier-frequency signals are transmitted simultaneously, if the spectrum of the target echo after channel separation can be combined to form the whole band spectrum echo, the corresponding range resolution can improve several times as compared with the conventional method, and it will be more convenient for follow-up detection and tracking. Considering the difference between the frequency modulation band and the interval between the adjacent frequencies, the spectrum joint after channel separation will be overlapped or spaced. The methods of spectrum moving of each echo and the spectrum extrapolation with Root-MUSIC algorithm are proposed, by which high-resolution range profile of the target is obtained. Simulation results verify the validity of these methods.

关键词： Multiple signal classification

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Moving object segmentation based on new likelihood functions

Moving object segmentation based on new likelihood functions

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IEEE International Symposium on Intelligent Signal processing and communication Systems (ISPACS)

作者： Xiang Zhang Zhi Liu Jie Yang Institute of Image Processing and Patter Recognition Shanghai Jiaotong University China Key Laboratory of Advanced Display and System Application Ministry of Education Shanghai University China

Accurate segmentation of moving objects from a video sequence is still a difficult task. A moving object segmentation method is proposed in this paper to deal with the segmentation splits and defects. First, it is claimed that the confusion point is one reason for the segmentation inaccuracy, and corresponding solution is also presented. According to the solution, new likelihood functions are proposed to compute membership probabilities, which are then used for final segmentation within an energy minimization framework. Unlike related algorithms which compute membership probabilities using kernel density estimation, the proposed method models the membership probabilities as functions with kernel density estimation as the independent variable. Experiments show that improved results are generated by the proposed likelihood functions.

关键词： Radio access networks

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