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

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An improved Mean Shift tracking algorithm based on color and texture feature 基于颜色和纹理特征的改进Mean Shift跟踪算法
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576453
Xiang Zhang, Yuan-Ming Dai, Zhang-wei Chen, Huai-Xiang Zhang
{"title":"An improved Mean Shift tracking algorithm based on color and texture feature","authors":"Xiang Zhang, Yuan-Ming Dai, Zhang-wei Chen, Huai-Xiang Zhang","doi":"10.1109/ICWAPR.2010.5576453","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576453","url":null,"abstract":"This paper presents an improved Mean Shift tracking algorithm. It extends the classic Mean Shift tracking algorithm by combining color and texture features. In the proposed method, firstly, both the color feature and the texture feature of the target are extracted from first frame and the histogram of each feature is computed. Then the Mean Shift algorithm is run for maximizing the similarity measure of each feature independently. In last step, center of the target in the new frame is computed through the integration of the outputs of Mean Shift. Experiments show that the proposed Mean-Shift tracking algorithm combining color and texture features provides more reliable performance than single features tracking.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"18 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":"115631354","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: 11
MWD drilling mud signal de-noising and signal extraction research based on the pulse-code information 基于脉冲码信息的随钻泥浆信号去噪与信号提取研究
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576341
Wen-Yuan Chen, Bin Fang, Yi Wang
{"title":"MWD drilling mud signal de-noising and signal extraction research based on the pulse-code information","authors":"Wen-Yuan Chen, Bin Fang, Yi Wang","doi":"10.1109/ICWAPR.2010.5576341","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576341","url":null,"abstract":"Mud pulse telemetry is a method used for Measurement-While-Drilling (MWD) in the oil industry. Information (tool face orientation, temperature, pressure, tilt, azimuth, etc.) which is modulated by means of pulse positioning modulation (PPM) is sent from the bottom of the well to the surface by means of pressure waves in the drilling fluid(the drilling mud). Due to external disturbances, the noise removal before decoding is of great importance for real-time monitoring of bottom hole. Wavelet transform has been used widely in signal de-noising. In this paper, a wavelet based de-noising technique is used to isolate the signals from the noise, and waveform shaping and signal extraction based on the pulse-code information are processed to restore pulse signal more fully and to improve the SNR. Results showed that the effect of the wavelet transform on signal de-noising suppression is good. While waveform reshaping and the signal extraction based on pulse-code information can be more accurate in restoring the pulse signal to facilitate future decoding.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"270 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":"114831087","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: 20
A new robust copyright protection scheme for digital image based on visual cryptography 一种新的基于视觉密码的数字图像鲁棒版权保护方案
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576465
Yin Xing, Jun He
{"title":"A new robust copyright protection scheme for digital image based on visual cryptography","authors":"Yin Xing, Jun He","doi":"10.1109/ICWAPR.2010.5576465","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576465","url":null,"abstract":"In this paper, a new digital image copyright protection scheme based on visual cryptography is proposed. Based on a more detailed feature classification in the discrete wavelet transform domain, an expanded code-book is used to improve the security of the current related schemes. Moreover, there is no need to modify the original image to be protected, which providing an obvious advantage when the image itself does not give permission for alteration. Experimental results show that the proposed scheme is robust against many common image processing attacks, such as JPEG compression, noise addition, cropping, rotation, scaling.","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":"124225221","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: 13
Contourlet-1.3 texture image retrieval system Contourlet-1.3纹理图像检索系统
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576449
Xinwu Chen, Guang-Li Yu, Junbin Gong
{"title":"Contourlet-1.3 texture image retrieval system","authors":"Xinwu Chen, Guang-Li Yu, Junbin Gong","doi":"10.1109/ICWAPR.2010.5576449","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576449","url":null,"abstract":"Contourlet transform has better performance in directional information representation than wavelet transform and has been studied by many researchers in retrieval systems and has been shown that it is superior to wavelet ones at retrieval rate. In order to improve the retrieval rate further, an anti-aliasing contourlet-1.3 transform based texture image retrieval system was proposed in this paper. In the system, the contourlet transform was constructed by anti-aliasing critical subsampled Laplacian pyramid cascaded by critical subsampled directional filter banks, sub-bands energy and standard deviations in contourlet domain are cascaded to form feature vectors, and the similarity metric is Canberra distance. Experimental results show that contourlet-1.3 transform based image retrieval system is superior to those of the original contourlet transform, nun-subsampled contourlet system and contourlet-2.3 under the same system structure with almost same length of feature vectors, retrieval time and memory needed; and anti-aliasing contourlet decomposition structure parameter can make significant effects on retrieval rates, especially scale number.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"62 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":"134057972","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: 9
A machine vision based crop rows detection for agricultural robots 基于机器视觉的农业机器人作物行检测
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576422
Guo-Quan Jiang, Cui-Jun Zhao, Yong-Sheng Si
{"title":"A machine vision based crop rows detection for agricultural robots","authors":"Guo-Quan Jiang, Cui-Jun Zhao, Yong-Sheng Si","doi":"10.1109/ICWAPR.2010.5576422","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576422","url":null,"abstract":"One approach of navigating agricultural robots to perform different kinds of operations such as weeding, spraying and fertilizing is using a machine vision based row detection system. A new method for robust recognition of crop rows is presented. First, image pre-processing was used to obtain the binarization image; second, the binarization image was divided into several row segments, which created less data points while still reserved information of crop rows; third, vertical projection method was presented to estimate the position of the crop rows for image strips; and last the crop rows were detected by Hough transform. The algorithm requires 70ms to determine all the crop rows. Experimental results show that this approach can quickly and accurately find the crop rows even under different light conditions.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"127 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":"125680890","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: 34
Image retrieval based on improved hierarchical clustering algorithm 基于改进层次聚类算法的图像检索
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576314
Cai_Yun Zhao, Bian-Xia Shi, Ming-xin Zhang, Zhao-Wei Shang
{"title":"Image retrieval based on improved hierarchical clustering algorithm","authors":"Cai_Yun Zhao, Bian-Xia Shi, Ming-xin Zhang, Zhao-Wei Shang","doi":"10.1109/ICWAPR.2010.5576314","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576314","url":null,"abstract":"The traditional CBIR is sequential retrieval. However, for large and high-dimension image databases, it is obvious that this retrieval method has been unable to meet efficiency. It is more important that the image database should be preprocessed and establish indexing to improve retrieval efficiency. Focus on the hierarchical clustering algorithm's high computational complexity, this paper introduces ART2 clustering algorithm for image database preprocessing, which reduces the computational complexity, and makes the Algorithm more efficient. In order to avoid the clustering center offset of ART2, K-means algorithm is used to calculate the pattern center, improving the accuracy of clustering. Compared by retrieval efficiency and retrieval result, it is convincingly proved that hierarchical index structure based on clustering is efficient and applicable in CBIR.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"58 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":"134422446","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
Semi-fragilewatermarking algorithm based on texture segmentation 基于纹理分割的半脆弱水印算法
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576433
Sheng-bing Che, Hanxu Gao, Jin Luo
{"title":"Semi-fragilewatermarking algorithm based on texture segmentation","authors":"Sheng-bing Che, Hanxu Gao, Jin Luo","doi":"10.1109/ICWAPR.2010.5576433","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576433","url":null,"abstract":"Based on texture visual features, region segmentation operator and quantization step equations were put forward. This guarantees the transparency of carrier image and the robustness of watermarking image extracted. After segmentation, the texture contour was clear, and the segmented results of smooth and texture region were satisfying. And it brought up the pixel value adjustment operator of IDWT. The basic idea of the algorithm is that after discrete wavelet transform, divided the low frequency coefficients LL into 2×2 blocks, then defined block coefficient suni ∑. If the value of ∑ was greater than the threshold, the block was segmented into texture area, or segmented into smooth area. When quantifying the step, the intensity and texture coefficient were considered, which made the transparency and robustness optimal. Experimental results showed that the result of texture segmentation was obviously better than the present algorithms. The pixel value could be adjusted by coefficient adjustment operator exactly. The carrier image had not only good transparency, but also better anti-attack capability.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"194 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":"123354566","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
Implement of electromagnetic pulse effects evaluation of radar system function module 雷达系统功能模块电磁脉冲效果评估的实现
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576342
Wan-Zhen Zhou, Jian-Xia Wang, Xin-Xin Liu, Jing-Fu Xue
{"title":"Implement of electromagnetic pulse effects evaluation of radar system function module","authors":"Wan-Zhen Zhou, Jian-Xia Wang, Xin-Xin Liu, Jing-Fu Xue","doi":"10.1109/ICWAPR.2010.5576342","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576342","url":null,"abstract":"Based on radar system function module 04-combination as the research object, this paper expatiates the establish process of the cross-neural network module of this module electromagnetic pulse action particularly, and designs evaluate system of this kind of electron system electromagnetic pulse effect, using the detailed process that BP-RBF cross neural network evaluation algorithm predicts this module. Finally, according to the evaluate experiment of 08- combination testing the effect of this evaluate system, results indicate that it is feasible that using this evaluate system evaluates electromagnetic pulse effect of electronic system.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"183 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":"124639262","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
Gear fault diagnosis based on SVM 基于支持向量机的齿轮故障诊断
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576299
Shangjun Ma, Geng Liu, Yongqiang Xu
{"title":"Gear fault diagnosis based on SVM","authors":"Shangjun Ma, Geng Liu, Yongqiang Xu","doi":"10.1109/ICWAPR.2010.5576299","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576299","url":null,"abstract":"Elements of Support Vector Machine was applied to the fault diagnosis of gear system, and the two-class algorithms for 3 individual fault modes, which are No Fault Gear Mode, Crack of Dedendum Mode and Tooth Surface Abrasion Mode respectively, are well developed and set up. Through the training and testing simulation data samples and the signal samples from gear oscillation, these 3 different types of gear fault modes are finally identified and distinguished from each other at the rotating speed of 300r/min and 900r/min. The result validates that the Support Vector Machine is with excellent diagnostic ability in the fault diagnosis system of gear and with favorable prospect in this filed of application.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"45 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":"124913460","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: 7
A new algorithm for infrared image restoration based on multi-scale morphological wavelet and Hopfield neural network 基于多尺度形态小波和Hopfield神经网络的红外图像恢复新算法
2010 International Conference on Wavelet Analysis and Pattern Recognition Pub Date : 2010-07-11 DOI: 10.1109/ICWAPR.2010.5576349
Jian-Hui Tan, Bao-chang Pan, Jian Liang, Yong-hui Huang, Xiao-yan Fan
{"title":"A new algorithm for infrared image restoration based on multi-scale morphological wavelet and Hopfield neural network","authors":"Jian-Hui Tan, Bao-chang Pan, Jian Liang, Yong-hui Huang, Xiao-yan Fan","doi":"10.1109/ICWAPR.2010.5576349","DOIUrl":"https://doi.org/10.1109/ICWAPR.2010.5576349","url":null,"abstract":"Based on the complexity and randomness of the infrared image degradation factors, and integrates the strong de-noising features of multi-scale morphological wavelet and the salient problem solving features of Hopfield neural network in optimization, this paper presents a new algorithm for infrared degraded image restoration. The algorithm takes advantage of the continuous recycle between \"multi-scale morphological wavelet de-noising\" and \"Hopfield neural network iteration\" so as to makes access to a better recovery of infrared images. The algorithm also solves the problems in noise suppression and image detail protection of traditional Hopfield neural network image restoration algorithm and successfully protects the edge of the recovery images and details. Simulation results prove the effectiveness of the recovery algorithm.","PeriodicalId":219884,"journal":{"name":"2010 International Conference on Wavelet Analysis and Pattern Recognition","volume":"10 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":"114745130","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
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