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

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A scene matching algorithm based on SURF feature 基于SURF特征的场景匹配算法
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476080
Su Juan, Xu Qingsong, Zhu Jinghua
{"title":"A scene matching algorithm based on SURF feature","authors":"Su Juan, Xu Qingsong, Zhu Jinghua","doi":"10.1109/IASP.2010.5476080","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476080","url":null,"abstract":"Scene matching has found important and wide applications in imaging guidance of cruise missile. A scene matching algorithm based on SURF feature is proposed in this paper. Firstly, SURF feature points are extracted respectively from base image and real-time image. Then, a coarse-to-fine matching method is used to realize the match of SURF feature points. The proposed algorithm has been tested on the collected image set. The experimental results shows that, compared with the frequently-used normal cross-correlation method, the proposed algorithm can process more complicated geometric deformations existed between base image and real image and acquire higher matching accuracy; compared with the matching algorithm based on SIFT feature, the proposed algorithm has lower computational burden and faster processing speed, which can meet the real-time requirements for scene matching.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"188 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":"114972407","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: 22
Feature extraction and soft segmentation of texture images 纹理图像的特征提取与软分割
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476094
Fang Li, Ruihua Liu, Chaomin Shen
{"title":"Feature extraction and soft segmentation of texture images","authors":"Fang Li, Ruihua Liu, Chaomin Shen","doi":"10.1109/IASP.2010.5476094","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476094","url":null,"abstract":"In this paper, we propose an efficient method for texture image segmentation. First we extract four feature channels smoothed with the total variation (TV) flow. Then we propose a soft segmentation model based on the Chan-Vese model by adding a weight in the arc length term and using a soft membership function in stead of level set function to represent the region. We derive a fast algorithm using the Additive Operator Scheme (AOS) and Chambolle's fast dual projection method. Experimental results on texture and Synthetic Aperture Radar (SAR) images show the effectiveness of our algorithm.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"37 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":"115070752","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
Components classification of the clastic rock thin-sections based on GIS 基于GIS的碎屑岩薄片组分分类
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476102
Bo Li, Tingshan Zhang, Liye Bai, Xiaoguang Miao
{"title":"Components classification of the clastic rock thin-sections based on GIS","authors":"Bo Li, Tingshan Zhang, Liye Bai, Xiaoguang Miao","doi":"10.1109/IASP.2010.5476102","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476102","url":null,"abstract":"The process of manual identification of thin-sections under the polarizing microscope is complex and repetitive. Geographic Information System (GIS) is a system of collecting, storing, managing, computing, analyzing, displaying and describing geospatial information. This paper proposes a way of recognizing and classifying components in clastic rock thin-sections image automatically using the spatial analysis and data management functions of GIS. The different components in clastic rock show different interference colors under orthogonal optical. According to the contrast differences between the components, we can extract the boundary of component and store it in a geodatabase through three steps including noise reduction, image segmentation and unsupervised classification. To deal with differences in size and shape of different component, we can use ISODATA(Iterative Organizing Analysis Technique) and MLC(Maximum Likelihood Classification) functions to classify and store the matrix. This paper provides a convenient tool for identifying, classifying and analyzing the thin-sections.","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":"129433017","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
Parameters analysis for polarimetric SAR Based on classification accuracy 基于分类精度的极化SAR参数分析
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476117
W. Xiaojun, Li-chun Hao, Wu Yonghui, Yan Shusheng, Lin Lianhua
{"title":"Parameters analysis for polarimetric SAR Based on classification accuracy","authors":"W. Xiaojun, Li-chun Hao, Wu Yonghui, Yan Shusheng, Lin Lianhua","doi":"10.1109/IASP.2010.5476117","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476117","url":null,"abstract":"As a multi-channel microwave remote sensing imaging radar system, polarimetric Synthetic Aperture Radar (SAR) enhances the information extraction ability for material scene in the observation area, in which the design and state monitoring for parameters play an important role in polarimetric SAR system and equipments management. This paper presents an analysis method for three typical polarimetric SAR system parameters: channel noise, polarization imbalance, and polarization isolation. We explore the polarimetric SAR image classification accuracy ratio and the relationship with three parameters above, review the statistic model of each parameter, and propose an analysis model between each parameter and the classification accuracy ratio measurement. By the polarimetric SAR image experiment, the comparative curve between each parameter and the influence on classification performance is obtained, which shows an application reference for polarimetric SAR system design and management.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"44 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":"128558213","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
Gesture segmentation based on monocular vision using skin color and motion cues 基于肤色和运动线索的单目视觉手势分割
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476096
Cao Xin-yan, Liu Hong-fei, Zou Ying-yong
{"title":"Gesture segmentation based on monocular vision using skin color and motion cues","authors":"Cao Xin-yan, Liu Hong-fei, Zou Ying-yong","doi":"10.1109/IASP.2010.5476096","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476096","url":null,"abstract":"Gesture segmentation is the first and the most critical step in sign language recognition. In this paper a method of gesture segmentation from the video image sequence based on monocular vision is presented by skin color and motion cues. Firstly, determine the background images and capture the gesture images with a sampling interval of 10 frames. Then with the difference method, the movement region of hand gestures is detected, meanwhile, through the analysis of the skin color information, the skin color region of hand gestures is obtained. After that, the initial gesture region can be gained by the AND operation on the movement region and the skin color region. Last but not least, gestures are separated from video image sequence reliably and completely using the mathematical morphology method. The experimental results indicate that the technique is capable of segmenting the gestures quite effectively.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"17 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":"128165843","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: 10
Edge-based text localization and character segmentation algorithms for automatic slab information recognition 基于边缘的文本定位和字符分割算法的平板信息自动识别
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476090
SungHoo Choi, J. Yun, Seungbo Sim, Sang Woo Kim
{"title":"Edge-based text localization and character segmentation algorithms for automatic slab information recognition","authors":"SungHoo Choi, J. Yun, Seungbo Sim, Sang Woo Kim","doi":"10.1109/IASP.2010.5476090","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476090","url":null,"abstract":"Content-based image indexing is to label image based on its content such as color, texture, shape, face, text, and etc. Because the text can be easily localized and recognized compared to other image contents, many researchers have studied about the general text localization in images actively. Generally, it is known that localizing scene text is more difficult than localizing caption text, and still it is not easy. However, although our target texts are scene texts, it is clear that they are not general, that is, the properties of target texts are fixed. In this paper, we propose an edge-based text localization and segmentation algorithms for automatic slab information recognition system.","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":"130016550","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
Parametric direction of arrival estimation in the small sample-size case 小样本情况下的参数到达方向估计
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476063
Manlin Xiao, Xin Qi, P. Wei
{"title":"Parametric direction of arrival estimation in the small sample-size case","authors":"Manlin Xiao, Xin Qi, P. Wei","doi":"10.1109/IASP.2010.5476063","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476063","url":null,"abstract":"The problem of direction of arrival estimation in array processing is considered in this paper. The focus is on how to estimate the source parameters accurately in the absence of a large number of snapshots. A parametric iterative adaptive algorithm based on amplitude and phase estimation with low computational complexities is proposed in this paper. Eigen-decomposition and the subspace projection are avoided in the proposed algorithm, such that the negative influence of subspace swap phenomena is weakened. This estimator is suitable for DOA estimation in the finite sample-size scenario, especially for resolving closely spaced sources. Numerical evaluations indicate that the estimator has a better performance than the MUSIC algorithm in the small sample-size scenario, where the observation dimension and the sample size are comparable in magnitude.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"47 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":"130484800","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
A novel image classification method based on manifold learning and Gaussian mixture model 一种基于流形学习和高斯混合模型的图像分类新方法
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476120
Xianjun Zhang, Min Yao, R. Zhu
{"title":"A novel image classification method based on manifold learning and Gaussian mixture model","authors":"Xianjun Zhang, Min Yao, R. Zhu","doi":"10.1109/IASP.2010.5476120","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476120","url":null,"abstract":"Image classification is one of the important parts of digital image processing. We propose a novel feature space-based image classification method by combining manifold learning and mixture model. In this paper, the process of image classification can be viewed as two parts: a coarse-grained classification and a fine-grained classification. In the coarse-grained classification, we apply the ISOMAP (Isometric Mapping) algorithm to do a dimensional reduction based on manifold learning. Thus, solving the classification problem is transformed from a high-dimensional data space to a low-dimensional feature space. And then, during the fine-grained classification, we present an improved EM algorithm of finite Gaussian mixture model to do clustering. Experimental results have demonstrated that the proposed method performs well in both accuracy and time. Additionally, our algorithm is robust to some extent.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"4 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":"125446596","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
An object-based change detection approach using high-resolution remote sensing image and GIS data 利用高分辨率遥感图像和GIS数据的基于目标的变化检测方法
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476052
Changhui Yu, Shaohong Shen, H. Jun, Yaohua Yi
{"title":"An object-based change detection approach using high-resolution remote sensing image and GIS data","authors":"Changhui Yu, Shaohong Shen, H. Jun, Yaohua Yi","doi":"10.1109/IASP.2010.5476052","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476052","url":null,"abstract":"This paper proposed an automatic approach to change detection using GIS data and remote sensing images. The approach is based on an object-based SVM classification. A pixel-merge segmentation algorithm using spectral information and area size is utilized to generate image objects. Samples are calculated using remote sensing image and historical land use vector data automatically. Then, an object-based SVM classification is used on remote sensing images. Object boundaries originated from GIS are basic elements to calculating class percentage in per region. Comparing class percentage and historical class property, if the class percentage is large and different to historical property, these regions are identified as changed. The paper first introduced the general approach, and then defined and discussed the spectral channels used for the classification. The results of test areas are followed. Finally, experimental results confirmed the advantages and efficiency of the proposed approach.","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":"126081160","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
Multi-beam steering for 3D audio rendering in linear phased loudspeaker arrays 线性相控扬声器阵列中三维音频渲染的多波束转向
2010 International Conference on Image Analysis and Signal Processing Pub Date : 2010-04-09 DOI: 10.1109/IASP.2010.5476169
Yongqing Tang, Yong Fang, Qinghua Huang
{"title":"Multi-beam steering for 3D audio rendering in linear phased loudspeaker arrays","authors":"Yongqing Tang, Yong Fang, Qinghua Huang","doi":"10.1109/IASP.2010.5476169","DOIUrl":"https://doi.org/10.1109/IASP.2010.5476169","url":null,"abstract":"In order to improve flexibility of surrounding stereo system, a novel system for 3D audio rendering is proposed in this paper based on multi-beam steering, which is composed of five beam units using linear loudspeaker arrays. By controlling accurately time delay or phase of loudspeakers, beam can be formed in a desired direction. The simulation results show that the proposed method is reasonable and effective.","PeriodicalId":223866,"journal":{"name":"2010 International Conference on Image Analysis and Signal Processing","volume":"21 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":"131215058","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
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