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Analysis of the electro-optical characteristics of thin film electroluminescent devices

Analysis of the electro-optical characteristics of thin film...

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作者： Xu, Jianbo Lou, Junhui Yang, Xin Xiao, Tian Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China Flat Panel Display Technology R and D Center SVA Electron Co. Ltd. 196 Ouyang Rd. Shanghai 200081 China

ISBN: (纸本)9787561752289

In this paper, we present the electro-optical characteristics of EL devices made by SVA. A Sawyer-Tower circuit has been set up to evaluate the luminous efficiency based on the measurements of luminance and transferred charge of the EL device. A program is developed to plot the luminance and efficiency as a function of voltage from the input of measurement data. These plots are useful for evaluating the performance of the EL devices and providing feedback for the optimization of thin film structure and processing parameters. When the modulation voltage is 30 V, it is shown that the luminance and efficiency of the yellow (ZnS: Mn) EL device is L30 =250 cd/m2 and η30 = 1.3 lm/W, respectively. Furthermore , the color spectra and the CIE color coordinates of various EL samples (green and blue) developed by SVA are evaluated and discussed.

关键词： Luminance

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On-line signature verification based on fusion of global and local information

On-line signature verification based on fusion of global and...

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International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Lei Hu Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

Automatic signature verification has been an intense research area because of the social and legal acceptance and widespread use of written signatures. It is still a challenging issue because of "small sample size " problem as well as large intra-class variations and, when considering forgeries, small inter-class variations. In order to solve these problems, we propose a two-stage fusion method to get high accuracy. At first, an EDTW (enhanced dynamic time warping) algorithm and a normalized feature measure are proposed to build a classifier based on local features. The former enhances the separability between genuine and forgery signatures, while the latter approaches the problem as a two-class pattern recognition problem, which make it possible to use training signatures as many as possible. However, local method is time and resource consuming, so we then design another classifier based on global features using majority voting rule. We fuse the global and local method by two-sage serial strategy to build an on-line signature verification system. Experimental results on SVC2004 TASK2 show good performance of our system.

关键词： Handwriting recognition pattern recognition Forgery Voting Wavelet analysis pattern analysis Law Legal factors Fuses

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Carrying object detection and tracking based on body main axis

Carrying object detection and tracking based on body main ax...

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International Conference on Wavelet Analysis and pattern recognition (ICWAPR)

作者： Yue Qi Guo-Chang Huang Yun-Hong Wang Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China

In this paper, we propose a method to examine whether a walking person is carrying objects using the width of human body contour. First we concentrate on the detection of the moving people contour and then human contour width is projected to the feature space for training a classifier. We introduce principal component analysis for dimension reduction and support vector machine to classify the carrying object status. If the status is true, the carrying object region is figured out by analyzing human contour shape. We utilize the outmost vertex from human contour to track the carrying object such as a rucksack or luggage. The experimental results demonstrate that our approach is encouraging.

关键词： Object detection Humans Principal component analysis Support vector machines Feature extraction Video sequences pattern recognition Legged locomotion Filtering Wavelet analysis

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Color image filtering based on impulsive noise detection

Color image filtering based on impulsive noise detection

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MIPPR 2007: Automatic Target recognition and image Analysis;and Multispectral image Acquisition

作者： Li, Dehua Jin, Lianghai Yao, Xingzhong Xiong, Caiquan State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Second Artillery Command College Wuhan 430012 China School of Computer Science Hubei University of Technology Wuhan 430068 China

ISBN: (纸本)9780819469502

This paper introduces a new class of switching vector median filter. The proposed algorithm first uses four directional masks to analyze the color difference between the central pixel and its neighborhood pixels in the RGB color space and classify each color pixel into noisy pixel or noise-free one, and then employs the standard vector median filtering operations in the detected noisy locations to restore the corrupted pixels and leave the noise-free ones unchanged. The simulation results show that the proposed method excellently suppresses impulsive noise as well as preserving the image details well, and significantly outperforms the existing vector filtering solutions in terms of both the objective measures and the perceptual visual quality.

关键词： Color image processing

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Moving Object Tracking from Videos Based on Enhanced Space-Time-Range Mean Shift and Motion Consistency

Moving Object Tracking from Videos Based on Enhanced Space-T...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Tiesheng Wang Irene Y.H. Gu Andrew Backhouse Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Signals and Systems Chalmers University of Technology Gothenburg Sweden

Video surveillance and object tracking have drawn increased interests in recent years. This paper addresses the problem of moving object tracking from image sequences captured from stationary cameras. Based on the previous work on video segmentation using joint space-time-range mean shift, we extend the scheme to enable the tracking of moving objects. Large displacements of pdf modes in consecutive image frames are exploited for tracking. We also improve the above mean shift-based video segmentation by introducing edge-guided merging of over-segmented regions. This can be viewed as an extension of the enhanced mean shift 2D image segmentation in [2] to the enhanced space-time-range mean shift video segmentation. Experiments have been conducted on several indoor and outdoor videos. Our preliminary results and performance evaluation have indicated the effectiveness of the proposed scheme.

关键词： Tracking Videos image segmentation Merging Kernel Cameras Object detection Change detection algorithms image processing pattern recognition

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image Quality Evaluation Based on No-reference Method with Visual Component Detection

Image Quality Evaluation Based on No-reference Method with V...

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International Conference on Natural Computation (ICNC)

作者： Li Zhu Guoyou Wang Laboratory for Biometric and Medical Image Processing Recognition & Artificial Intelligence Huazhong University of Science and Technology Wuhan China

In this paper, we present a new image quality assessment that does not rely on reference images. Our model is to estimate human quality assessment by detecting visual components, then assessing quality by empirical model. We describe an instance of this model with visual component detection, and quality modeling is estimated using radial basis function (RBF) networks. Experiments with this prototype system show better results for human visual system(HVS).

关键词： image quality Humans Quality assessment Face detection Object detection Biometrics Biomedical image processing image recognition Artificial intelligence Visual perception

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Local Structure Detection with Orientation-invariant Radial Configuration

Local Structure Detection with Orientation-invariant Radial ...

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Conference on Computer Vision and pattern recognition (CVPR)

作者： Lech Szumilas Rene Donner Georg Langs Allan Hanbury Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria

Local image descriptors have proved themselves as useful tools for many computer vision tasks such as matching points between multiple images of a scene and object recognition. Current descriptors, such as SIFT, are designed to match image features with unique local neighborhoods. However, the interest point detectors used with SIFT often fail to select perceptible local structures in the image, and the SIFT descriptor does not directly encode the local neighborhood shape. In this paper we propose a symmetry based interest point detector and radial local structure descriptor which consistently captures the majority of basic local image structures and provides a geometrical description of the structure boundaries. This approach concentrates on the extraction of shape properties in image patches, which are an intuitive way to represent local appearance for matching and classification. We explore the specificity and sensitivity of this local descriptor in the context of classification of natural patterns. The implications of the performance comparison with standard approaches like SIFT are discussed.

关键词： Detectors Shape Computer vision Layout Object recognition

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Face recognition System Using Ant Colony Optimization-Based Selected Features

Face Recognition System Using Ant Colony Optimization-Based ...

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IEEE Symposium on Computational Intelligence in Security and Defense Applications, CISDA

作者： Hamidreza Rashidy Kanan Karim Faez Mehdi Hosseinzadeh Image Processing and Pattern Recognition Laboratory Electrical Engineering Department Tehran Polytechnic Amirkabir University of Technology슠 Tehran Iran Department of Computer Engineering University of Isfahan Isfahan Iran

Feature selection (FS) is a most important step which can affect the performance of pattern recognition system. This paper presents a novel feature selection method that is based on ant colony optimization (ACO). ACO algorithm is inspired of ant's social behavior in their search for the shortest paths to food sources. In the proposed algorithm, classifier performance and the length of selected feature vector are adopted as heuristic information for ACO. So, we can select the optimal feature subset without the priori knowledge of features. Simulation results on face recognition system and ORL database show the superiority of the proposed algorithm

关键词： Face recognition Ant colony optimization Discrete wavelet transforms pattern recognition Artificial intelligence Particle swarm optimization Computational intelligence Computer security Application software image processing

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Video Content Representation by Incremental Non-Negative Matrix Factorization

Video Content Representation by Incremental Non-Negative Mat...

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IEEE International Conference on image processing

作者： Serhat S. Bucak Bilge Gunsel Multimedia Signal Processing and Pattern Recognition Laboratory Det. of Electronics and Communication Engineering Istanbul Technical University Istanbul Turkey

Nonnegative matrix factorization (NMF) is a powerful decomposition tool which has been used in several content representation applications recently. However, there are some difficulties in implementing NMF in on-line video applications. This paper introduces an incremental NMF (INMF) without deviating from conventional NMF"s main objective function, which is minimizing the reconstruction error. The proposed algorithm is capable of modeling dynamic content of the video; thus controls contribution of the subsequent observations to the NMF representation properly. It is shown that the INMF preserves additive, parts-based representation capability of the NMF with a low computational load while offering dimension reduction. Experimental results are given to compare the reconstruction performances of the conventional and incremental NMF. In addition, video scene change detection and dynamic video content representation by INMF are investigated. Test results demonstrate that the INMF can be used as a powerful on-line factorization tool.

关键词： Matrix decomposition Layout Testing

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Normalized Linear Transform for Cross-Platform Microarray Data Integration

Normalized Linear Transform for Cross-Platform Microarray Da...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Huilin Xiong Ya Zhang Xue-wen Chen Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS USA

With microarray data being dramatically accumulated, integrating data from related studies represents a natural way to increase sample size so that more reliable statistical analysis may be performed. However, inherent variation among different microarray platforms makes the data integration not a trivial task. In this paper, we present a simple and effective integration scheme, called normalized linear transform (NLT), to combine data from different microarray platforms. The NLT scheme is compared with three other integration schemes for two tasks: classification analysis and gene marker selection. Our experiments demonstrate that the NLT scheme performs best in terms of classification accuracy under various classification settings, and leads to more biologically significant marker genes.

关键词： Costs Gene expression Support vector machines Support vector machine classification Machine learning Application software image processing pattern recognition Computer science Statistical analysis

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