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International Conference on Multimedia Technology

作者： Yiren Xu Fujian Wang Yuming Zhao Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper presents a three-step framework to remove the highlight exists on objects in certain conditions. Unlike traditional HDR (High Dynamic Range) technology requires multiple registrated image sequence; our method needs only two arbitrary images. SURF (Speeded Up Robust Features) matching algorithm is first applied to find corresponding point pairs between images; homography is then found by perspective transformation theory; minimum gray selection is used at last to eliminated the highlight and fuse related regions. Experimental results are given to demonstrate the performance of our method.

关键词： Feature extraction image color analysis Robustness Dynamic range Plastics Pixel Color

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The role of context and model in urban aerial image interpretation focusing on buildings

The role of context and model in urban aerial image interpre...

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IEEE International Conference on Networking, Sensing and Control

作者： Jing Peng Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0780381939

Guided by a building concept model, which interprets building into different levels and scales, this paper presents a method to extract buildings in monocular urban aerial images without priori illuminating or orientation knowledge. By using a shadow context model, a method was proposed to estimate the direction of shadow cast to verify the raw segmentations. Building extractions are refined by context, and a method of partial snake with the aid of the shadow cast direction is proposed, which can sharply reduce the iteration complexity and the influence caused by illumination. The extraction of self-shadow on gable roof with a proposed mathematical roof model is also discussed in this paper.

关键词： Context modeling Buildings Data mining image edge detection Urban areas Lighting Geographic Information Systems Radiometry image processing pattern recognition

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Blind bilevel image restoration using Hopfield neural networks

Blind bilevel image restoration using Hopfield neural networ...

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International Conference on Neural Networks

作者： H.-J. Liu Y. Sun Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

A Hopfield neural network approach to blind bilevel image restoration is presented. In the approach, two kinds of Hopfield neural networks are used. One is the analog Hopfield neural network, utilized to estimate the parameters of the finite point spread function (PSF) of a blurring system. The other one is the modified Hopfield neural network used to restore bilevel image. The entire model is based on the alternative operation of the two networks. In the modified Hopfield neural network, the eliminating highest error (EHE) criterion is applied for the purpose of obtaining a more precise solution. Simulation results show that, after a few iterations, the model always obtains a bilevel image whose quality is almost the same as, or even better than, what is obtained by the modified Hopfield network when the precise parameters of PSF are used. The results are quite good. If the EHF criterion is not used, the model does not achieve a good bi-level image.< >

关键词： image restoration Hopfield neural networks Parameter estimation Degradation Convolution Sun image processing pattern recognition Neural networks Mathematics

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A new adaptive diffusion equation for image noise removal and feature preservation

A new adaptive diffusion equation for image noise removal an...

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International Conference on pattern recognition

作者： Shoushui Chen Xin Yang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

Anisotropic diffusion can remove noise to some extent in image processing. However the contradiction between diffusion and preservation still exists. In this paper, a new nonlinear diffusion model for image noise removal and feature preservation is presented. This model treats inhomogeneity region and image feature adaptively by discontinuity measure and local gradient information. A well balance between diffusion and preservation is also made in this new diffusion method. Experiments results show that the proposed method has high performance compared to other literature methods and is an ideal edge-preserving filtering method. In addition, we use block-based noise estimation to estimate deviation in diffusion equation

关键词： Equations Additive noise Smoothing methods image processing pattern recognition Filtering Low pass filters Anisotropic magnetoresistance Pollution measurement Noise reduction

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Hierarchical interactive image segmentation using irregular pyramids

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6658 LNCS卷 245-254页

作者： Gerstmayer, Michael Haxhimusa, Yll Kropatsch, Walter G. Pattern Recognition and Image Processing Group Institute of Computer Graphics and Algorithms Vienna University of Technology Austria

ISBN: (纸本)9783642208430

In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from different (granularity) levels are combined to a final (better) segmentation with user-specified operations guiding the segmentation process. Based on these operations the users can produce a final image segmentation that best suits their applications. This work can be used for applications where we need accuracy in image segmentation, in annotating images or creating ground truth among others. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： image segmentation

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The Del /sup 2/G performance in the presence of noise

The Del /sup 2/G performance in the presence of noise

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International Conference on pattern recognition

作者： Xie Zhaohui Wu Lide Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0818608781

The Laplacian of Gaussian operator, Del /sup 2/G, is very important as an edge detector in the theory of computer vision. The bias of zero-crossing and output signal-to-noise-ratio of Del /sup 2/G under the models of four typical kinds of edges corrupted by white noise are given, and these theoretical results are confirmed by experiments. The relations among bias of zero-crossing, output and input signal-to-noise-ratio and parameter sigma of Del /sup 2/G are presented.< >

关键词： Detectors Filtering White noise Proposals Performance analysis image edge detection Pulse shaping methods Kernel Shape

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Unconstrained handwritten numeral recognition using Hausdorff distance and multi-layer neural network classifier

Unconstrained handwritten numeral recognition using Hausdorf...

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International Conference on Document Analysis and recognition

作者： Xuejing Wu Pengfei Shi Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769503187

A method for zip code recognition is presented. 2D binary images are input to HAVNET, a neural network which employs the Hausdorff distance as a similarity metric to train the weights which are required to represent the patterns learned by the network. A new learning rule for HAVNET is also introduced. In this approach, HAVNET is combined with a multilayer neural network. The Hausdorff distance acts as a zip code filter. Only the confusing digits are input into the multilayer network for training or recognition. Experimental results show that the correct-recognition rate with zero rejection is more than 97% for a database used by the Chinese mail sorting system.

关键词： Handwriting recognition Neural networks Multi-layer neural network pattern recognition Shape Optical character recognition software Euclidean distance image recognition Optical filters Postal services

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A PC algorithm for dynamic actuated traffic-control system

A PC algorithm for dynamic actuated traffic-control system

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International Conference on Intelligent Transportation

作者： Xingyu Zheng Zhonghua Liu Yuncai Liu InstituteImage Processing and Pattern Recognition University of Shanghai Jiaotong China Institute Image Processing and Pattern Recognition University of Shanghai Jiaotong China Department of the lost Imaging Processing and Pattern Recognition University of Shanghai Jiaotong China

ISBN: (纸本)0780381254

In this paper, we analyze the traditional algorithm (Circle->Phase) in the traffic-control system. And we propose a new algorithm that is proved better than the former one. By traffic flow simulation using advanced TSIS software, we get statistic data to analyze the characteristic of downstream traffic flow (DTF). Based on the mathematic model of DTF, we bring forward an algorithm to quickly decide the phase length and circle length. The algorithm adopts the real-time information according to required flow with the aim of minimizing the surplus time in each phase. It can adapt to any kind of traffic flow and has a high degree of flexibility.

关键词： Heuristic algorithms Traffic control Delay effects Algorithm design and analysis Analytical models Vehicle detection image recognition Road transportation Vehicle dynamics Statistical analysis

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Multisensor aerial image registration using direct histogram specification

Multisensor aerial image registration using direct histogram...

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IEEE International Conference on Networking, Sensing and Control

作者： Hongya Tuo Lin Zhang Yuncai Liu Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

Multisensor image registration is a difficult problem. In this paper, we give a new registration method using direct histogram specification technique. We find that after using histogram specification, the resulting images with the same view look more similar, though the original images gained by different sensors differ much in intensity. Based on this property, a novel approach to find matching block pairs is proposed. The centers of the block pairs are used as control points (cps). We also use the cluster method of the nearest function criterion to test the correctness of the cps and discard wrong ones. The algorithm has been tested by many aerial images of different sensors. The effectiveness is illustrated by the experimental results.

关键词： image registration Histograms image sensors pattern recognition Remote sensing image processing Satellites Testing Feature extraction Sensor phenomena and characterization

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Facial Components Detection with Boosting and Geometric Constraints

Facial Components Detection with Boosting and Geometric Cons...

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International Conference on pattern recognition

作者： Tiesheng Wang Pengfei Shi Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769525210

An efficient framework utilizing both local features and geometrical distribution for detecting facial components is presented. First, candidate facial components are efficiently collected by cascaded boosting of Haar-like features. The candidates may include false positives and multiple detections. Then, geometrical distribution of facial components is imposed on the candidates to select the optimal configuration. For simplicity, we suppose full dependence between the components and model it with multivariate Gaussian. The effectiveness of the framework is evaluated with experiments

关键词： Face detection Boosting pattern recognition image processing Humans Eyes Mouth Nose Shape Face recognition

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