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Improving depth resolution of diffuse optical tomography with an exponential adjustment method based on maximum singular value of layered sensitivity

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Chinese Optics Letters 2008年第12期6卷 886-888页

作者：牛海晶郭平宋晓东蒋田仔 Image Processing and Pattern Recognition Laboratory Beijing Normal University School of Computer Science and Technology Beijing Institute of Technology School of Aerospace Science and Engineering Beijing Institute of Technology National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences

The sensitivity of diffuse optical tomography （DOT） imaging exponentially decreases with the increase of photon penetration depth, which leads to a poor depth resolution for DOT. In this letter, an exponential adjustment method （EAM） based on maximum singular value of layered sensitivity is proposed. Optimal depth resolution can be achieved by compensating the reduced sensitivity in the deep medium. Simulations are performed using a semi-infinite model and the simulation results show that the EAM method can substantially improve the depth resolution of deeply embedded objects in the medium. Consequently, the image quality and the reconstruction accuracy for these objects have been largely improved.

关键词： Diagnostic radiography Electroabsorption modulators image quality Light absorption Medical imaging Optical tomography

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image segmentation based on visual perception model

Image segmentation based on visual perception model

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2012 2nd International Conference on Computer Application and System Modeling, ICCASM 2012

作者： Shao, Shuai Duan, Fuqing Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9789491216008

image segmentation is the basis of image processing and image analysis. However, there are no common method that can be used in natural images, and present methods fail to explain understandings of human's visual system. In this paper, we propose to apply Karklin's visual perception model to extract feature vectors of images, and the features are clustered with K-means method. The results obtained in feature space are projected back to the image space to finish segmentation. A comparison with the normalized Cuts (Ncut) method is done, and it turns out that proposed method outperform Ncut in texture rich images. © the authors.

关键词： image segmentation

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Software fault prediction framework based on aiNet algorithm

Software fault prediction framework based on aiNet algorithm

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2011 7th International Conference on Computational Intelligence and Security, CIS 2011

作者： Yin, Qian Luo, Ruiyi Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9780769545844

Software fault prediction techniques are helpful in developing dependable software. In this paper, we proposed a novel framework that integrates testing and prediction process for unit testing prediction. Because high fault prone metrical data are much scattered and multi-centers can represent the whole dataset better, we used artificial immune network (aiNet) algorithm to extract and simplify data from the modules that have been tested, then generated multi-centers for each network by Hierarchical Clustering. The proposed framework acquires information along with the testing process timely and adjusts the network generated by aiNet algorithm dynamically. Experimental results show that higher accuracy can be obtained by using the proposed framework. © 2011 IEEE.

关键词： Forecasting

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Combining the contrast information with WLD for texture classification

Combining the contrast information with WLD for texture clas...

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2012 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2012

作者： Dawood, Hussain Dawood, Hassan Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781467300865

A considerable amount of research work has been done for texture classification using local or global feature extraction methods. Inspired by Weber's Law, a simple and robust Weber Local Descriptor (WLD) is a recently developed for local feature extraction. This WLD method did not consider the contrast information. In order to improve texture classification accuracy, we propose a hybrid approach that combines the WLD with contrast information in this paper. It utilizes the histogram of two complementary features WLD and the image variance calculated with the Probability Weighted Moments. Support vector machine is used for classification. The comparison of the proposed method with state of art methods like local binary pattern and WLD is experimental investigated on two publically available dataset, named as Brodatz and KTH-TIPS2-a. Results show that our proposed method outperforms over the state of art methods for texture classification. © 2012 IEEE.

关键词： Support vector machines

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Isomap and neural networks based image registration scheme

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Xu, Anbang Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)3540344373

A novel image registration scheme is proposed. In the proposed scheme, the complete isometric mapping (Isomap) is used to extract features from the image sets, and these features are input vectors of feedforward neural networks. Neural network outputs are those translation, rotation and scaling parameters with respect to reference and observed image sets. Comparative experiments for Isomap based method, the discrete cosine transform (DCT) and Zernike moment are performed. The results show that the proposed scheme is not only accurate but also remarkably robust to noise. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Self organizing maps

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Global matching to enhance the strength of local intensity order pattern feature descriptor

Global matching to enhance the strength of local intensity o...

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10th International Symposium on Neural Networks, ISNN 2013

作者： Dawood, Hassan Dawood, Hussain Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)9783642390647

Local intensity order pattern feature descriptor is proposed to extract the feature of image recently. However, it did not provide the global information of an image. In this paper, a simple, efficient and robust feature descriptor is presented, which is realized by adding the global information to local intensity features. A descriptor, which utilizes local intensity order pattern and/or global matching, is proposed to gather the global information with local intensity order. Experimental results shows that the proposed hybrid approach outperform over the state-of-the art feature extraction method like scale-invariant feature transform, local intensity order pattern and DAISY for standard oxford dataset. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Feature extraction

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Rendering scenes with participating media based on RBFs for photon mapping using graphics hardware

Rendering scenes with participating media based on RBFs for ...

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12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry, VRCAI 2013

作者： Wang, Yuanlong Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)9781450325905

The photon mapping is one of the more widely used algorithms for rendering scenes with participating media. Currently, it suffers from two main problems: one is how to improve the rendering efficiency, and another is how to reduce large memory requirement to store the photons. In this paper, we propose a hardware-accelerated algorithm that is based on radial basis function model for rendering participating media with multiple scattering. The radial basis function model is used to describe the photon distribution in participating media, and the main purpose is to provide high reconstruction quality using a relatively low number of basis function terms. Consequently, it can result in faster rendering. The radiance estimation is designed according to the radial basis function model. The implementation demonstrates that proposed method is the attractive low memory representation and it is capable of fully simulating the scattering of participating media with interactive feedback to the user. © 2013 ACM.

关键词： Radial basis function networks

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Software-based non-invasive geometric correction of projector

Software-based non-invasive geometric correction of projecto...

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2nd Workshop on Digital Media and its Application in Museum and Heritage, DMAMH 2007

作者： Tong, Gao Xin, Zheng Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)0769530656

Curved screens are often used in virtual reality vision systems. But distortion happens when projecting on a curved surface. Some special projectors and equipment have been invented to solve this problem. Instead of using such expensive hardware equipment, we propose a software-based non-invasive geometric correction method in this paper, which can rectify the distorted image projected on any curved screen interactively without modifying source code. For applications based on OpenGL, we make a new *** to intercept the OpenGL API functions (especially SwapBuffer) in Windows operating system's library search path. And most of our rectification was implemented in the function we wrote to substitute the original SwapBuffer. Considering different demands from different users, we leaved the picture quality and the response time of the system controllable. © 2007 IEEE.

关键词： Virtual reality

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Two-dimensional PCA combined with PCA for neural network based image registration

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2nd International Conference on Natural Computation, ICNC 2006

作者： Xu, Anbang Jin, Xin Guo, Fing Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)3540459073

A novel image registration scheme is proposed. In the proposed scheme, two-dimensional principal component analysis (2DPCA) combined with principal component analysis (PCA) is used to extract features from the image sets and these features are fed into feedforward neural networks to provide translation, rotation and scaling parameters. Comparison experiments between 2DPCA combined with PCA based method and the other two former methods: discrete cosine transform (DCT) and Zernike moment, are performed. The results indicate that the proposed scheme is both accurate and remarkably robust to noise. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Principal component analysis

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Software-based non-invasive implementation of binocular vision

Software-based non-invasive implementation of binocular visi...

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International Conference on Computer Science and Software Engineering, CSSE 2008

作者： Tong, Gao Xin, Zheng Qian, Yin Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

ISBN: (纸本)9780769533360

In this paper, we present a software-based noninvasive system to implement binocular stereo vision with the help of polarized glass or other auxiliary equipments. For any application based on OpenGL, our system can give its binocular vision by displaying its original scene as projecting one frame from the left viewpoint and the next frame from the right viewpoint alternately to simulate the imaging on left eye and right eye. Focus and pupillary distance are two parameters in the implementation which we can set manually. By the way of making a new *** to substitute the old one to intercept the OpenGL API functions, we can change the projection matrix and modify the rendering flow non-invasively by overloading some OpenGL API functions without modifying the application's source code. © 2008 IEEE.

关键词： Auxiliary equipment

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