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2010 International Conference on Wavelet Analysis and Pattern Recognition最新文献

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Multi-dimensional time series-based application server aging model 基于多维时间序列的应用服务器老化模型
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576346
Wenbin Xu, Yong Qi, Di Hou
{"title":"Multi-dimensional time series-based application server aging model","authors":"Wenbin Xu, Yong Qi, Di Hou","doi":"10.1109/ICWAPR.2010.5576346","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576346","url":null,"abstract":"To observe and study the performance degradation of the application server, client-request programs and server monitoring programs are designed for different scenarios to record different parameters — five categories and 36 parameters altogether. In this paper, primary component analysis method is adopted to reduce dimension, and then multi-dimensional time series analysis method used to set up a model-based on key performance parameter of application server middleware. The statistical result of analyzing the measured data shows that the predicting values derived from the multi-dimensional time series-based application server aging model can match the initial data very well, and that the predicting precision is obviously improved in contrast with the one-dimensional auto regression model. So the aging model may well be adopted for real time predicting of run-time system and its predicting result can be further used as the trigger of system maintenance follow-up action.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116121448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A study on a class of two-direction orthogonal wavelets on compact Lie groups 紧李群上一类双向正交小波的研究
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576357
Baoqin Wang, Gang Wang, L. Yuan
{"title":"A study on a class of two-direction orthogonal wavelets on compact Lie groups","authors":"Baoqin Wang, Gang Wang, L. Yuan","doi":"10.1109/ICWAPR.2010.5576357","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576357","url":null,"abstract":"In this paper, by virtue of the methods which comes from intersecting and combining differential geometry with wavelet theory, and this method belong to us. We extend the two-direction multiresolution and the two-direction Mallat Algorithm to the theory on the special differential manifold — compact Lie group, our work lay a foundation for the further study wavelet theory on compact Lie group.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"552 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117025244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fracture identification of X-ray image x射线图像的断裂识别
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576438
Jian Liang, Bao-chang Pan, Yong-hui Huang, Xiao-yan Fan
{"title":"Fracture identification of X-ray image","authors":"Jian Liang, Bao-chang Pan, Yong-hui Huang, Xiao-yan Fan","doi":"10.1109/ICWAPR.2010.5576438","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576438","url":null,"abstract":"This article proposes a method to identify fractures in human X-ray photos. According to the characteristics of X-ray image, the high-order statistical moments adopted to verify segmentation have been combined with partial threshold method to segment bone image. After the segmentation, mathematical morphology will be applied to extract the target border and cover the boundary of fractures. By superposing the target border image and covering the extracted skeleton, the precise location of fractures can be recognized and therefore the fractures in the X-ray photos will be identified.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130857923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Gait recognition using sparse representation 基于稀疏表示的步态识别
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576306
Yan Ma
{"title":"Gait recognition using sparse representation","authors":"Yan Ma","doi":"10.1109/ICWAPR.2010.5576306","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576306","url":null,"abstract":"A new approach of gait recognition based on sparse representation is proposed. Static and motion information are fused using the averaged boundary which is extracted by canny operator. The training data and the testing data belong to one object when there is a sparse representation in training data for the testing data. The algorithm is implemented on USF gait database. Experimental results prove the higher performance of the method on the gait datasets which are captured on different time.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"9 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133060146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Image denoising using multi-scale thresholds method in the wavelet domain 基于小波域多尺度阈值法的图像去噪
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576434
Ming Tian, Hao Wen, Long Zhou, Xinge You
{"title":"Image denoising using multi-scale thresholds method in the wavelet domain","authors":"Ming Tian, Hao Wen, Long Zhou, Xinge You","doi":"10.1109/ICWAPR.2010.5576434","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576434","url":null,"abstract":"Images often contain noise due to the capturing devices, environment and even human errors. For the image further processing, compression, fractal and so on, the image denoising is necessary. Wavelet analysis plays a very important role in the image denoising. In this paper, we improve the wavelet thresholding method by using multi-scale thresholds and a new thresholding function. Also, in case of large noise, a median Alter is suggested to be used at last. Based on Lipschitz exponent and wavelet transform, we theoretically give the multi-scale thresholds. In order to obtain a better denoising result, We also present a new thresholding function instead of the hard or soft thresholding function. Experiment results show that our improved method gives a higher PSNR and has less visual artifacts compared with other methods.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122807597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Generic ring fourier descriptors for shape description 形状描述的一般环傅里叶描述子
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576441
Jianwei Yang, Xiang-Jun Zhao, Rushi Lan
{"title":"Generic ring fourier descriptors for shape description","authors":"Jianwei Yang, Xiang-Jun Zhao, Rushi Lan","doi":"10.1109/ICWAPR.2010.5576441","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576441","url":null,"abstract":"The traditional Fourier descriptor (FD) can only be used to objects with single boundary. We develop a novel method, Generic Ring Fourier Descriptor (GRFD), which can be applicable to gray-scale image. Firstly, we take an unconventional view of the traditional FDs, as we treat the boundary as a closed-curve in a 2-D binary image. Consequently, the generated FD (GFD) is proposed such that it can be applicable to a closed-curve with gray value in an image. Then GFD is applied to concentric circles with different radius in the image and GRFDs are derived. Objects can be represented by these GRFDs which are invariant to translation, scaling and rotation. Experiments using images from the coil-20 database have been conducted to compare the performance of the proposed descriptors with Hu's moments and Complex moments (CMs). The proposed method demonstrated superior performance.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"117 2S 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123078794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
The real-time gpr signals preprocessing algorithm based on LWT in high scan rate 高扫描率下基于LWT的探地雷达实时信号预处理算法
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576345
Gan Lu, Zhou Long
{"title":"The real-time gpr signals preprocessing algorithm based on LWT in high scan rate","authors":"Gan Lu, Zhou Long","doi":"10.1109/ICWAPR.2010.5576345","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576345","url":null,"abstract":"In this work, we use DSP mechanism for real-time Ground Penetrating Radar (GPR)data preprocessing assess in high scan-rate scenarios. The lifting wavelet transform-based algorithm takes the advantages of efficient computation and memory reduction and is a suitable solution for DSP real-time implementation. In addition, the parallel operations technique on DSP memory is applied to enhance the system efficiency. Such that we realize a 3-level pipeline data structure which can significantly release the signal preprocessing time from the data collecting and data display time etc. The experimental results demonstrate the effectiveness of the developed scheme for real-time GPR data processing.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122225158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A new image denoising method based on BEMD and self-similar feature 一种基于BEMD和自相似特征的图像去噪方法
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576462
Jianjia Pan, Yuanyan Tang
{"title":"A new image denoising method based on BEMD and self-similar feature","authors":"Jianjia Pan, Yuanyan Tang","doi":"10.1109/ICWAPR.2010.5576462","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576462","url":null,"abstract":"This paper presents a new method for image denoising through Bi-dimensional Empirical Mode Decomposition (BEMD). Although there have been many filter based methods for image processing, problems of non-adaptively and redundancy are still hard to solve. The BEMD is a locally adaptive method and suitable for the analysis of nonlinear or non-stationary signals. The image can be decomposed to several IMFs (intrinsic mode functions) by BEMD, which present new characters of the images. But for the BEMD, the boundary interference is a main limit for its application. In this paper, we firstly proposed a new BEMD method based on the self-similar extend method and the neighbor local extremes to reduce the boundary interference. And then based on the new BEMD method, a denoising algorithm based on the new BEMD is proposed.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127660532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Foreground/background difference saliency via information maximization for moving target detection 基于信息最大化的前景/背景差分显著性运动目标检测
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576445
Zhi-Lin Ni, J. Lai, Xian Wu
{"title":"Foreground/background difference saliency via information maximization for moving target detection","authors":"Zhi-Lin Ni, J. Lai, Xian Wu","doi":"10.1109/ICWAPR.2010.5576445","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576445","url":null,"abstract":"This paper proposes a novel method for moving target detection using foreground/background difference saliency via information maximization. Information maximization saliency map of the current frame is first generated to highlight the moving targets. To reduce the negative effects from the clutter scene, saliency map recording the interference factors is also constructed for a static background, and the moving target is detected based on the difference saliency, rather than the traditional background subtraction. In order to calculate better basis functions for saliency, we update constantly training samples for basis functions using background salient regions. The experimental results of our method are very encouraging, especially in the complex scene with many camera jitters and background disturbances etc.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132495231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An efficient casts recognition algorithm in urinary sediment images 一种有效的尿沉渣图像模型识别算法
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-01 DOI: 10.1109/ICWAPR.2010.5576450
Xue-Qin Yang, Bin Fang, Jun-feng Xiong
{"title":"An efficient casts recognition algorithm in urinary sediment images","authors":"Xue-Qin Yang, Bin Fang, Jun-feng Xiong","doi":"10.1109/ICWAPR.2010.5576450","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576450","url":null,"abstract":"A new and efficient method for casts recognition in urinary sediment microscopic images is proposed in this paper. It combines the shape and texture characteristics of casts, and accordingly, consists of two steps. In the first step, the casts' tube-like shape feature is expressed by a modified method stems from the traditional one which is based on the minimum bounding rectangle(MBR). Instead of using MBR, we make use of the centerline to describe its shape while curved casts are concerned. Then, in the next step, some texture features are extracted and send to the SVM classifier for further judgment. As this method is quite focus on the features of casts, both shape and texture, it is very effective to recognize casts in urinary sediment images. Large experiments proved that this method is easy to implement and achieves high accuracy.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"113 s1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132477411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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