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2010 International Conference on Image Analysis and Signal Processing最新文献

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Improved PGA algorithm based on adaptive range bins selection 基于自适应距离箱选择的改进PGA算法
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476125
Yuan Deng, Yunhua Zhang
{"title":"Improved PGA algorithm based on adaptive range bins selection","authors":"Yuan Deng, Yunhua Zhang","doi":"10.1109/IASP.2010.5476125","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476125","url":null,"abstract":"Phase gradient autofocus (PGA) algorithm has been proved to be a superior method for higher order phase error correction in SAR/ISAR image post processing. However, the accuracy of phase error estimation using traditional PGA algorithm is usually not guaranteed especially when there are several strong adjacent scatterers in a range bin. In this paper an improved iterative PGA approach based on adaptive range bins selection is presented. Results of real data experiments show that the improved PGA algorithm outperforms the traditional one.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130331914","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: 5
Study of fabric defects detection through Gabor filter based on scale transformation 基于尺度变换的Gabor滤波器织物疵点检测研究
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476155
Shuyue Chen, Jun Feng, Ling Zou
{"title":"Study of fabric defects detection through Gabor filter based on scale transformation","authors":"Shuyue Chen, Jun Feng, Ling Zou","doi":"10.1109/IASP.2010.5476155","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476155","url":null,"abstract":"Aiming at fabric defects detection in textile industry, a Gabor filtering strategy based on scale transformation was presented, in which the extension scale of Gabor filter function was shown. Firstly the Gabor filter banks are convolved with normal fabric image to extract normal texture features. Secondly the convolution of Gabor filter banks and defected image is carried out to obtain the deviation images, and then they are fused. Lastly the fabric defects are detected by threshold processing. The results show that the method is effective for fabric defects detecting.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114253030","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
A new method of target recognition based on Rough Set and Support Vector Machine 基于粗糙集和支持向量机的目标识别新方法
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476053
Zhi-jun Guo, Xin He, Zhonghui Wei, G. Liang
{"title":"A new method of target recognition based on Rough Set and Support Vector Machine","authors":"Zhi-jun Guo, Xin He, Zhonghui Wei, G. Liang","doi":"10.1109/IASP.2010.5476053","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476053","url":null,"abstract":"Automatic target recognition (ATR) is an important task in image application. This paper concentrates on two key subroutines of ATR system: Pre-treatment and design of classifier. In the pre-treatment subroutine, a new method based on Rough Set (RS) is proposed to partition the original sample set into some subsets and calculate their class membership, so that some samples can be chosen by class membership to be trained. After pre-treatment, an iterative algorithm based on Rough Set and Support Vector Machines (IRSSVM) is introduced to design a classifier for recognizing two types of targets. The experiment results show that IRSSVM needs less training time and the classifier is simpler and has more generalization and higher recognition rate.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114583418","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
Robust image watermarking using dual tree complex wavelet transform based on Human Visual System 基于人眼视觉系统的双树复小波鲁棒图像水印
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476180
Jinhua Liu, Kun She
{"title":"Robust image watermarking using dual tree complex wavelet transform based on Human Visual System","authors":"Jinhua Liu, Kun She","doi":"10.1109/IASP.2010.5476180","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476180","url":null,"abstract":"In this paper, we proposed an image watermarking algorithm based on Human Visual System's perceptual model in the dual tree complex wavelet domain. We took advantages of the regular and the complex wavelets (perfect reconstruction, approximate shift invariance, and good directional selectivity) for watermark embedding. Firstly we applied the JND (Just Noticeable Difference) to control the watermark embedding strength. Then the host image was decomposed into six sub-bands by the 4-level dual tree complex wavelet transform. We embedded the watermark sequence into the six subbands with the same JND value. Lastly the watermark was extracted by comparing the host image coefficients and the watermarked image coefficients. Experimental results confirm that the proposed method was robust against geometric distortions, Gaussian noise, JPEG compression and Gaussian low pass filtering attacks.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117198433","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
Detecting and tracking of small moving target in avian radar images 鸟类雷达图像中小运动目标的检测与跟踪
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476073
Weishi Chen, Huansheng Ning, L. Jing
{"title":"Detecting and tracking of small moving target in avian radar images","authors":"Weishi Chen, Huansheng Ning, L. Jing","doi":"10.1109/IASP.2010.5476073","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476073","url":null,"abstract":"A sequence of plane position indicator (PPI) images containing a small moving target is collected using an experimental avian radar surveillance system, which is constructed by modifying a standard marine radar. Smoothing trajectory of a small moving target is separated from the image sequence after background subtraction, clutter suppression, measurements extraction and tracking. The background image is generated by Fast Independent Component Analysis (FastICA). Low segmentation value is set in clutter suppression to improve detecting rate at the cost of introducing a great deal of clutters. Therefore, false alarm rate need to be reduced by tracking. Meanwhile, a modified Hough transform method is applied for track initiation. Monte Carlo data association is proposed for track maintenance and Kalman filtering is adopted for target state prediction and update. Finally, the trajectory is smoothed and then fused with a satellite map for further observation.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115885161","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
Radar mosaic based on the explicit radar ray paths 基于显式雷达射线路径的雷达拼接
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476070
He Jian-xin, Deng Yong, Li Zheng, Wu Rong
{"title":"Radar mosaic based on the explicit radar ray paths","authors":"He Jian-xin, Deng Yong, Li Zheng, Wu Rong","doi":"10.1109/IASP.2010.5476070","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476070","url":null,"abstract":"In radar observation, different ray paths, which influence the three-dimensional gridding process, is due to the different gradients of reflectivity. The earth's radius model, which could not describe the radar ray path in a certain atmospheric thermodynamic condition, is the average condition of the radar ray pathway. In order to get the mosaic data of a certain thermodynamic condition, we need an arithmetic that could produce mosaic data based on the explicit radar ray paths. In this paper, we propose a method enable us to get the mosaic data based on any certain thermodynamics profiles of atmosphere. And the results are compared to the products of radar mosaic scheme based on the fixed earth's radius model in a certain atmospheric thermodynamic condition.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123056136","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
Automatic classification algorithm of urban building based on corner analysis 基于转角分析的城市建筑自动分类算法
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476051
Yang Miao, Gong Cheng-long
{"title":"Automatic classification algorithm of urban building based on corner analysis","authors":"Yang Miao, Gong Cheng-long","doi":"10.1109/IASP.2010.5476051","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476051","url":null,"abstract":"An automatic type estimation method of the urban building is presented in this paper. This work analyzes the corner characteristic of common city buildings. Using morphological sieves of large scale, rough building contours are obtained. This method uses the segments and corners optimization to group each corner, and realizes the automatic differentiation between flat roof building and non-flat building. Finally, simulation examples show the validity and effectiveness of the proposed method.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129815593","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
Computer vision-based multiple-lane detection on straight road and in a curve 基于计算机视觉的直道和弯道多车道检测
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476151
Yan Jiang, F. Gao, Guoyan Xu
{"title":"Computer vision-based multiple-lane detection on straight road and in a curve","authors":"Yan Jiang, F. Gao, Guoyan Xu","doi":"10.1109/IASP.2010.5476151","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476151","url":null,"abstract":"A vision system was designed to detect multiple lanes on structured highway using an “estimate and detect” scheme. It detected the lane in which the vehicle was driving (the central lane) and estimated the possible position of two adjacent lanes. Then the detection was made based on these estimations. The vehicle was first recognized if it was driving on a straight road or in a curve using its GPS position and the OpenStreetMap digital map. The two cases were processed differently. For straight road, the central lane was detected in the original image using Hough transformation and a simplified perspective transformation was designed to make estimations. In the case of curve path, a complete perspective transformation was performed and the central lane was detected by scanning at each row in the top view image. The system was able to detected lane marks that were not distinct or even obstructed by other vehicles.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127266366","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: 77
Contourlet transform based algorithm of shadow compensation for face recognition 基于Contourlet变换的阴影补偿人脸识别算法
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476183
Haitao Yu, Huorong Ren, Yan Kai
{"title":"Contourlet transform based algorithm of shadow compensation for face recognition","authors":"Haitao Yu, Huorong Ren, Yan Kai","doi":"10.1109/IASP.2010.5476183","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476183","url":null,"abstract":"This paper researches of the new multi-scale geometric analysis tool—Contourlet and proposes a new Contourlet multi-threshold method of shadow compensation for uneven illumination face images. The proposed algorithm combines hard threshold with 2D shadow compensation method and selects proper thresholds depending on the sub-band layers of Contourlet transform. It takes full advantage of the shadow elimination with Contourlet multi-threshold method and the 2D shadow compensation method, so that it could obtain the information of the shadow field and non-shadow field. Experiments are carried out using the Yale B database and the results demonstrate that the face images dealt with the proposed method have good subjective vision and impersonal identify ratio. For images under different illumination angles, compared with 2D shadow compensation algorithm, the proposed method has an average recognition ratio increase of 21.20% to 55.84% in extreme condition.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121113659","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
An improved DFT-SOFDM scheme based on inter-carrier interference cancellation 基于载波间干扰消除的改进DFT-SOFDM方案
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476083
Jinwang Yi, En Cheng, Haixin Sun, Fei Yuan
{"title":"An improved DFT-SOFDM scheme based on inter-carrier interference cancellation","authors":"Jinwang Yi, En Cheng, Haixin Sun, Fei Yuan","doi":"10.1109/IASP.2010.5476083","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476083","url":null,"abstract":"In this paper, a novel and efficient improved spectrum allocation scheme of DFT-SOFDM in a frequency selective channel is presented. The proposed scheme exploits data conjugate mapping on the basis of inter-carrier interference (ICI) cancellation, which has low complexity but high performance. The illustrative examples over Least Square (LS) and Linear Minimum Mean-Squared Error (LMMSE) equalization demonstrate that the proposed scheme can achieve better BER and Peak to Average Power Ratio (PAPR) performance compared to the conventional distributed spectrum allocation scheme in DFT-SOFDM system.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"286 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122302131","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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