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检索条件"机构=Jiangsu Provincial Key Lab. of Image Processing and Image Communication"

共 91 条记录，以下是21-30 订阅

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Optimal approximation of head-related transfor function based on adaptive genetic algorithm

Optimal approximation of head-related transfor function base...

引用

2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Xuelong, Hu Yan, Tang Jun, Cai School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China

ISBN: (纸本)9781424423118

Head-related Transfer Functions (HRTFs) refer to the spectral filtering from sound sources to listeners' eardrums or ear canals. As an effective model structure, the degree of the IIR filter approximation of the HRTFs, whose design and implementation is a specific spectrum function approximation process, is much lower than that of the FIR. Based on the assessment of HRTFs different importance for sound sources recognition in different spectrum bands, and associated with some perspectives of psychoacoustics in spatial hearing, adaptive and revalued coding genetic algorithm (GA) is applied to the approximation of the HRTFs zero-pole model. The results show that, on an average, the performance of adaptive GA is better than that of the traditional GA. ©2008 IEEE.

关键词： Transfer functions

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image retrieval based on character-matching technology

Image retrieval based on character-matching technology

引用

5th International Conference on Information Assurance and Security, IAS 2009

作者： Shan, Zhao Jing, Liu School of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China

ISBN: (纸本)9780769537443

In order to introduce effective text-retrieval technologies into content-based image retrieval, a novel method based on string-matching technology was presented incorporating the different sensitivity along variant directions of human visual system. The image is firstly divided into non-overlapped blocks and sub-feature is extracted according to the human visual feature. Then, a novel descriptor is defined. Based on which, the sub-features is mapping into characters and the image into the text. Finally, the technology of the character string matching is adopted as the similarity measurement. Meantime, the situation information of character is considered, an adjusted method is proposed. Experimental results show that the proposed method has sound and robust retrieval performance. © 2009 IEEE.

关键词： Content based retrieval

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Approaches to image retrieval using fuzzy set theory

Approaches to image retrieval using fuzzy set theory

引用

2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Li, Yang Xuelong, Hu Jun, Pan School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Jiangsu Prov. Key Lab. for Computer Information Processing Technology Suzhou University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424423118

This paper mainly presents two approaches for image retrieval. There is some faintness in color locating in quantification boundary when image color is quantized. The membership function in fuzzy set theory can describe the fuzzy transition preferably. In this paper, the membership function in HSI color space is adopted to solve the problem above. At the same time, spatial information is integrated with color feature to describe the image content more truly. Due to the importance of texture feature, gray concurrence matrix is extracted. In the second part of this paper, retrieval scheme combining four image feature descriptors is presented, and then follows Fuzzy Hamming Distance (FHD) which is used as a fuzzy similarity measure. We have performed an experiment on a 1000 images database and our results show higher retrieval accuracy. © 2008 IEEE.

关键词： Fuzzy sets

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Mixed image de-noising method of Bayesian estimation and wavelet based on alpha-stable distribution

Mixed image de-noising method of Bayesian estimation and wav...

引用

2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Zhijian, Wang Xuelong, Hu Cheng, Li Liping, Wang School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Yangzhou Jiangsu 225001 China

ISBN: (纸本)9781424423118

This paper introduces a new kind of recovery method which is the combination of Bayesian estimation and wavelet threshold. Wavelet coefficients of signals show strong characteristics of the non-Gauss statistics, its probability density function can be modeled by alpha-stable priori distribution. This paper uses Bayesian estimation to obtain the low frequency coefficients, and deals with high frequency coefficients with the wavelet soft threshold, then restore signal by wavelet inverse transform. Bayesian estimation well retains the marginal information of signals, but the signal is still not very smooth recovery and wavelet soft threshold can maintain smooth characteristic. The mixed noise elimination methods of Bayesian estimation and wavelet enhance the peak SNR much greater than wavelet threshold, which has better recovery effect. ©2008 IEEE.

关键词： Probability density function

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image retrieval based on bit-plane distribution feature

Image retrieval based on bit-plane distribution feature

引用

6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Shan, Zhao Jing, Lui School of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Prov. Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China

ISBN: (纸本)9780769537351

Based on the analysis of color histogram for image retrieval, a new descriptor, bit-plane distribution feature(BPDF), is proposed in this paper. The image is firstly divided into eight bit-planes. Meantime, the Gray code of bit-planes is used to avoid the effect of changes in the intensity values on bit-planes. Then, according to the distribution of each bit-plane, a feature vector is constructed by the first four significant planes which contain most of the structural information of the image. Finally, the Mahalanobis distance is adopted to measure the similarity because of the correlation between the concerned vectors after designing a correlation-weighted matrix. Comparisons are conducted between BPDF and other descriptors. Experimental results show that the proposed method provides more significantly retrieval results than the traditional ones. © 2009 IEEE.

关键词： image retrieval

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Error concealment for stereoscopic images using mode selection

Error concealment for stereoscopic images using mode selecti...

引用

International Symposium on Intelligent Signal processing and communications Systems

作者： Song, Lijuan Zhu, Xiuchang State Grid Electric Power Research Institute Nanjing 210003 China Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781424473717

In this paper, a novel error concealment (EC) method for compressed stereoscopic image pairs is presented, which contains a new binocular EC mode and an improved monocular EC mode. The proposed algorithm selects appropriate EC mode to conceal the error block (EB) in the stereoscopic image according to the local characteristic of the EB. The experimental results demonstrate that the proposed scheme has good subjective and objective EC performance in stereoscopic images as compared to monocular mode. © 2010 IEEE.

关键词： Errors

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Adaptive resampling in particle filter based on diversity measures

Adaptive resampling in particle filter based on diversity me...

引用

International Conference on Computer Science and Education

作者： Yu, Jin-Xia Liu, Wen-Jing Tang, Yong-Li College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab. of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781424460052

It is very important to find a criterion when to perform a resampling step. Aimed at this problem, an adaptive resampling algorithm in particle filter based on diversity measures is presented. Based on the analysis and comparison of two diversity measures that are effective sample size (ESS) and population diversity factor(PDF), the resampling algorithm based on ESS is introduced. On the basis of that, PDF is used for adaptively tuning the resampling threshold. At last, with the simulation program using matlab.7.0 to track a single target motion from a fixed visual observation points, the performance of the proposed algorithm is evaluated and its validity is verified. ©2010 IEEE.

关键词： MATlab

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A camera self-calibration method based on dual constraints of multi-view images

A camera self-calibration method based on dual constraints o...

引用

2011 International Conference on Wireless communications and Signal processing, WCSP 2011

作者： Liu, Feng Han, Weiwei Xu, Qiong Lin, Qiongjie Fan, Jingjing Image Processing and Image Communication Jiangsu Key Laboratory Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781457710100

Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera self-calibration method based on dual constraints of multi-view images is proposed to make calibration possible when there is no reference calibration block or the movement of camera is arbitrary. In this method, multi-view images are preprocessed first to select three images which are most suitable for camera self-calibration, then we use the method based on the genetic algorithm, the camera parameters are finally estimated by using epipolar geometry matching error and reprojection error as fitness functions as two steps. Experimental results show that the proposed camera self-calibration method is correct and effective. © 2011 IEEE.

关键词： Genetic algorithms

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Vehicle color recognition using monocular camera

Vehicle color recognition using monocular camera

引用

2011 International Conference on Wireless communications and Signal processing, WCSP 2011

作者： Yang, Mengjie Han, Guang Li, Xiaofei Zhu, Xiuchang Li, Liang Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing Univ. of PandT Nanjing China Engineering Research Center of Wideband Wireless Communication and Display Technique Ministry of Education Nanjing Univ. of PandT Nanjing China

ISBN: (纸本)9781457710100

This paper introduces a novel moving vehicle color recognition method. By processing videos recorded by monocular camera on traffic, we get single color image of vehicles which are crossed the traffic in any direction. First, paper employed a H-S two dimension histogram method to detect the color of the vehicles, and distinguish red, yellow, green and blue four color vehicles. Due to deal with the vehicles that do not satisfy above 4 colors, Regional Color Judgment method is proposed. This method consists of the following five steps: Firstly, position the color detection region by identifying the travelling direction of the vehicle. Then pick out the candidate color extraction region used to vehicle recognition. At last extract the color of the candidate region and match the color with the templates we predefined, the color of the best fit template is the color of the vehicle. © 2011 IEEE.

关键词： Color

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Video object matching based on sift algorithm

Video object matching based on sift algorithm

引用

2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Xuelong, Hu Yingcheng, Tang Zhenghua, Zhang School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Prov. Key Lab for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Jiangsu Prov. Key Lab. for Computer Information Processing Technology Suzhou University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424423118

SIFT (Scale Invariant Feature Transform) is used to solve visual tracking problem, where the appearances of the tracked object and scene background change during tracking. The implementation of this algorithm has five major stages: scale-space extrema detection;keypoint localization;orientation assignment;keypoint descriptor;keypoint matching. From the beginning frame, object is selected as the template, its SIFT features are computed. Then in the following frames, the SIFT features are computed. Euclidean distance between the object's SIFT features and the frames' SIFT features can be used to compute the accurate position of the matched object. The experimental results on real video sequences demonstrate the effectiveness of this approach and show this algorithm is of higher robustness and real-time performance. It can solve the matching problem with translation, rotation and affine distortion between images. It plays an important role in video object tracking and video object retrieval. © 2008 IEEE.

关键词： Tracking (position)

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