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2013 Seventh International Conference on Image and Graphics最新文献

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An Improved Method Based on CV and Snake Model for Ultrasound Image Segmentation 基于CV和Snake模型的超声图像分割改进方法
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.38
Li Qianqian, Li Qingyi, Lihua Lei, Fu Yingxia, Bai Peirui
{"title":"An Improved Method Based on CV and Snake Model for Ultrasound Image Segmentation","authors":"Li Qianqian, Li Qingyi, Lihua Lei, Fu Yingxia, Bai Peirui","doi":"10.1109/ICIG.2013.38","DOIUrl":"https://doi.org/10.1109/ICIG.2013.38","url":null,"abstract":"In recent years, active contour models have become one of hotspots in the field of image segmentation. However, for ultrasound images, it is difficult to achieve ideal segmentation results with those methods that only based on boundary information or regional information. In this paper, we combined GVF-Snake with CV model. First, preliminary segmentation is implemented with CV model. Then, the local information in each object area is optimized with GVF-Snake. The experimental results demonstrate the proposed method can effectively deal with image blur and edge break in ultrasound images. The resulting contours are relatively intact and close to the manual results.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121249125","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
Improved Video Denoising Algorithm Based on Spatial-Temporal Combination 基于时空组合的改进视频去噪算法
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.19
Hong-Zhi Wang, Chen Ling, Shu-Liang Xu
{"title":"Improved Video Denoising Algorithm Based on Spatial-Temporal Combination","authors":"Hong-Zhi Wang, Chen Ling, Shu-Liang Xu","doi":"10.1109/ICIG.2013.19","DOIUrl":"https://doi.org/10.1109/ICIG.2013.19","url":null,"abstract":"An algorithm of video denoising based on spatial-temporal combination is proposed to improve the video quality. This algorithm can adaptively distinguish the still regions from the motion regions of video frames by bilateral motion detection of multiple frames, where temporal bilateral Kalman filtering is applied to the still regions and spatial bilateral adaptive Nonlocal means (ANL) filtering is applied to the motion regions. Experimental results show that by making full use of the spatial-temporal information of video, the proposed algorithm can significantly improve the peak signal-to-noise ratio (PSNR) and the subjective video quality without movement ghosting. Besides, the speed of video denoising can be accelerated by bilateral filtering.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"76 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116247600","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
Inter-slice Resolution Improvement of Lung 4D-CT via Adaptively Patch Partition and Sparse Representation 基于自适应补丁分割和稀疏表示的肺部4D-CT片间分辨率提高
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.30
Yu Zhang, Lei Cao, Qianjin Feng, Wufan Chen
{"title":"Inter-slice Resolution Improvement of Lung 4D-CT via Adaptively Patch Partition and Sparse Representation","authors":"Yu Zhang, Lei Cao, Qianjin Feng, Wufan Chen","doi":"10.1109/ICIG.2013.30","DOIUrl":"https://doi.org/10.1109/ICIG.2013.30","url":null,"abstract":"Lung four-dimensional computer tomography (4D-CT) data resolution enhancement is helpful for lung cancer accurate radiotherapy. Sparse representation based algorithm has been proposed to reconstruct the resolution enhancement image, and achieved state-of-art performance. In this paper, based on the sparse representation algorithm, we present an adaptively patch partition approach to divide the slices into adaptively scaled patches. This approach will catch more anatomical nuances and improve the reconstruction. The quad tree-based algorithm is employed in our method to partition the slices. Moreover, a jointly intensity-feature homogeneity is defined to determinate the patch division criterion. The effectiveness of the proposed method is demonstrated by the experiments.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116305423","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 Transductive Transfer Learning Method for Ship Target Recognition 舰船目标识别的一种传递学习方法
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.90
Zhiping Dan, N. Sang, Ruolin Wang, Yanfei Chen, X. Chen
{"title":"A Transductive Transfer Learning Method for Ship Target Recognition","authors":"Zhiping Dan, N. Sang, Ruolin Wang, Yanfei Chen, X. Chen","doi":"10.1109/ICIG.2013.90","DOIUrl":"https://doi.org/10.1109/ICIG.2013.90","url":null,"abstract":"Ship target recognition in infrared image remains a difficult problem, due to the projection or silhouette of a three-dimensional ship target being variable in shape, orientation and scale to make its recognizability unstable. In this paper, a transductive transfer learning framework is proposed to solve the problem. Hu moments is firstly extracted as feature vectors of target. Then the transductive transfer learning method is used to find the common parameters between the feature spaces of the training ship samples and the detected ship targets, and transfer the similar knowledge from those data with different distributions. According to the experiment result in simulation infrared images, it shows that the ship targets can be recognized highly and reliably by our proposed framework. It demonstrates the robustness and effectiveness of our method for infrared images.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122014802","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
Classification Related Manifold Dimension Estimation with Restricted Boltzmann Machine 基于受限玻尔兹曼机的分类相关流维估计
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.174
K. Teng, Jinqiao Wang
{"title":"Classification Related Manifold Dimension Estimation with Restricted Boltzmann Machine","authors":"K. Teng, Jinqiao Wang","doi":"10.1109/ICIG.2013.174","DOIUrl":"https://doi.org/10.1109/ICIG.2013.174","url":null,"abstract":"To handle high dimensional variables in real world, especially multimedia data, dimension reduction techniques provide effective solutions for feature selection which makes the problem easy to deal in a lower dimension subspace. However, the primary problem with traditional dimension reduction method is to estimate intrinsic dimension of manifold supporting the raw data. Since all existing approaches of dimension reduction need to set the target dimension first. And for task of classification, the dimension we need maybe different from the intrinsic one, which means feature with intrinsic dimension may offer too much information for the classification task. In this paper, we propose a method to estimate classification related dimension with the help of RBM (Restricted Boltzmann Machine) and SVM classifiers. RBM is used for dimension reduction by mapping raw data to a low dimensional hidden space, and SVM classifier is used to test information preserving ability of this hidden space. An optimal dimension is selected as the minimum one that preserves all the classification related information of novel vectors. Further, a novel initialization strategy is proposed to speed up the training of RBM. These new methods are with low time consumption and memory cost compared to many other approaches of dimension estimation. Experiments and comparisons on several synthetic and realistic datasets show the superiority of the proposed method.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116139708","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
GVF Snake Based Target Contour Extraction in SAR Imagery 基于GVF Snake的SAR图像目标轮廓提取
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.44
Xin Zhou, Pei Wang, Congqing Wang, Yongqiang Ye
{"title":"GVF Snake Based Target Contour Extraction in SAR Imagery","authors":"Xin Zhou, Pei Wang, Congqing Wang, Yongqiang Ye","doi":"10.1109/ICIG.2013.44","DOIUrl":"https://doi.org/10.1109/ICIG.2013.44","url":null,"abstract":"Target contour provides valuable shape information that can be used in pose estimation, target recognition, etc., which makes contour extraction a hot research topic. Gradient vector flow (GVF) snake has been proved to be an efficient method for extracting target contour. Due to the existence of speckle noise, direct applying GVF snake for extracting target contour in synthetic aperture radar (SAR) imagery is not successful. Based on the characteristics of SAR imagery, a method of using GVF snake for extracting target contour in SAR imagery is proposed. The proposed method first computes a likelihood ratio image in which the contrast between target and background is enhanced, and then a line-drawing edge map is generated based on the computed likelihood ratio image, finally GVF snake extracts the target contour by using the generated edge map. The experimental results on the real SAR image have demonstrated the effectiveness of the proposed method.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126023448","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
Visual Servoing of Mobile Robots with Sphere Objects 球面对象移动机器人的视觉伺服
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.136
Baoquan Li, Yongchun Fang, Xuebo Zhang
{"title":"Visual Servoing of Mobile Robots with Sphere Objects","authors":"Baoquan Li, Yongchun Fang, Xuebo Zhang","doi":"10.1109/ICIG.2013.136","DOIUrl":"https://doi.org/10.1109/ICIG.2013.136","url":null,"abstract":"The problem that using visual feedback to control the distance and orientation of the mobile robot with respect to a static sphere object is considered in this paper. Firstly, a unit virtual sphere is added on the classical camera model to obtain accurately the direction of the object. After measurable signal analysis, the kinematics model of the system is obtained. Then a switched controller and a continuous adaptive controller are developed to drive the mobile robot to the desired pose. Lastly, in order to estimate the distance between the camera and the object, a nonlinear observer is designed to give an exact estimation for the radius of the object, thus no metric information of the object is needed. Simulation results are collected to validate the effectiveness of the proposed method.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125727254","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
The LogitBoost Based on Joint Feature for Face Detection 基于联合特征的LogitBoost人脸检测
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.97
Shishi Duan, Xiangyang Wang, W. Wan
{"title":"The LogitBoost Based on Joint Feature for Face Detection","authors":"Shishi Duan, Xiangyang Wang, W. Wan","doi":"10.1109/ICIG.2013.97","DOIUrl":"https://doi.org/10.1109/ICIG.2013.97","url":null,"abstract":"In this paper, joint Haar-like feature is used for detecting faces in images. Our method is based on the co-occurrence Haar-like features which can capture the structural characteristic of the face, make it possible to construct more effective weak classifier. As the Haar-like, the joint Haar-like feature can be calculated very effective and has the robustness to addition of noise and change in illumination. The face detector is learned by stage wise selection which is different with Viola and Jones Detector is that we use LogitBoost. We perform two experiments: In the Experiment 1, we show that the LogitBoost [9] obtain higher performance than AdaBoost [2] [4] [11]. We have confirmed that our method based on LogitBoost yielded higher performance than AdaBoost. In the Experiment 2, the performance increase according with the num of the combined features. However, the time spent increase at huge growth rate, too. Therefore, we will research that how we can choose the optimal F at the acceptable training time in the latter work.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131196702","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
Principal Directions Estimation on Point Set Surfaces 点集曲面的主方向估计
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.49
Chen He, Yan Zhang, Xue-qing Li
{"title":"Principal Directions Estimation on Point Set Surfaces","authors":"Chen He, Yan Zhang, Xue-qing Li","doi":"10.1109/ICIG.2013.49","DOIUrl":"https://doi.org/10.1109/ICIG.2013.49","url":null,"abstract":"Principal direction is an important geometry feature of 3D surfaces. It can benefit many applications such as surface quadrangulation, surface field design and so on. In this paper, we propose a novel algorithm for estimating principal directions based on normal variations. The proposed algorithm is based on the observation that the principal directions indicate respectively the slowest and the steepest variation of the surface normal. The algorithm is simple yet efficient. It doesn't need any analytic surface fitting procedure. The result shows that our algorithm is correct and suitable for different surface shapes.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131504667","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 Novel Image Registration Algorithm in Aerial Infrared Videos 一种新的航空红外视频图像配准算法
2013 Seventh International Conference on Image and Graphics Pub Date : 2013-07-26 DOI: 10.1109/ICIG.2013.120
Chenxu Wang, Shuxiao Li, Yiping Shen, Hao Shen, Hongxing Chang
{"title":"A Novel Image Registration Algorithm in Aerial Infrared Videos","authors":"Chenxu Wang, Shuxiao Li, Yiping Shen, Hao Shen, Hongxing Chang","doi":"10.1109/ICIG.2013.120","DOIUrl":"https://doi.org/10.1109/ICIG.2013.120","url":null,"abstract":"This paper focuses on image registration between sequential frames in aerial infrared video. To address this problem, we propose an efficient approach based on an improved Smallest Univalue Segment Assimilating Nucleus (SUSAN) corner detector and a novel corner rejection strategy. Firstly, the SUSAN corners are detected via the concatenation of enlarging the radius of original detector and down-sampling. Then, the corner rejection strategy is applied to remove the corners on moving objects. After that, Histograms of Oriented Gradients (HOG) is used to form the descriptor of each corner, followed by a feature matching phase to obtain correspondences of corners. Finally, RANdom Sample Consensus (RANSAC) is performed to estimate the parameters of the transformation model with the correspondences. Experimental results show that our approach is fast and stable for image registration in aerial infrared videos.","PeriodicalId":425822,"journal":{"name":"2013 Seventh International Conference on Image and Graphics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133278448","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
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