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2010 IEEE International Conference on Image Processing最新文献

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Approximation of digitized curves with cubic Bézier splines 用三次bsamizier样条逼近数字化曲线
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5651820
Alexander Kolesnikov
{"title":"Approximation of digitized curves with cubic Bézier splines","authors":"Alexander Kolesnikov","doi":"10.1109/ICIP.2010.5651820","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5651820","url":null,"abstract":"In this paper we examine a problem of digitized curves approximation for raster graphics vectorization and develop an efficient implementation of a near-optimal Dynamic Programming algorithm for digitized curves approximation with cubic Bézier splines for a given distortion bound. For better fitting performance, we introduce the inflection points with relaxed constraint of tangent continuity. The proposed algorithm demonstrates superiority over the iterative breakpoint-insertion method in terms of segments number for a given distortion bound.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133413854","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
Color transfer via local binary patterns mapping 颜色转移通过局部二进制模式映射
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5653671
Chen Yao, Xiaokang Yang, Li Chen, Jian Wang
{"title":"Color transfer via local binary patterns mapping","authors":"Chen Yao, Xiaokang Yang, Li Chen, Jian Wang","doi":"10.1109/ICIP.2010.5653671","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5653671","url":null,"abstract":"Color transfer is a process of carrying over image colors from one image to another. Since images have diverse texture, color, content and other features, key challenge for color transfer is to find a correct mapping between image and target image. In this paper, a new color transfer method based on feature points extraction and local binary patterns(LBP) mapping is proposed. We construct a framework for feature points extraction and mapping. In the framework, we use SIFT descriptor for feature points selection and we design a LBP mapping method for feature points matching between source and target image. Final feature points in source image are obtained using this mapping. Greyscale source image and final feature points are used as inputs of a scribble-based colorization method to get the final color transfer result. Experimental results show the benefits of our method.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133675769","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
Human Activity Recognition via 3-D joint angle features and Hidden Markov models 基于三维关节角度特征和隐马尔可夫模型的人体活动识别
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5651953
Md. Zia Uddin, N. Thang, Tae-Seong Kim
{"title":"Human Activity Recognition via 3-D joint angle features and Hidden Markov models","authors":"Md. Zia Uddin, N. Thang, Tae-Seong Kim","doi":"10.1109/ICIP.2010.5651953","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5651953","url":null,"abstract":"This paper presents a novel approach of Human Activity Recognition (HAR) using the joint angles of the human body in 3-D. From each pair of activity video images acquired by a stereo camera, the body joint angles are estimated by co-registering a 3-D body model to the stereo information: our approach uses no attached sensors on the human. The estimated joint angle features from the time-sequential activity video frames are then mapped into codewords to generate a sequence of discrete symbols for a Hidden Markov Model (HMM) of each activity. With these symbols, each activity HMM is trained and used for activity recognition. The performance of our joint angle-based HAR has been compared to that of the conventional binary silhouette-based HAR, producing significantly better results in the recognition rate: especially for those activities that are not discernible with the conventional approaches.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132145314","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: 25
An MRF framework for joint registration and segmentation of natural and perfusion images 一种用于自然图像和灌注图像联合配准和分割的磁共振成像框架
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5651441
D. Mahapatra, Ying Sun
{"title":"An MRF framework for joint registration and segmentation of natural and perfusion images","authors":"D. Mahapatra, Ying Sun","doi":"10.1109/ICIP.2010.5651441","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5651441","url":null,"abstract":"Registration and segmentation provide complementary information about each other. In this paper we propose a method for the joint registration and segmentation (JRS) of images using Markov random fields (MRFs). The use of MRFs allows us to formulate the problem as one of labeling and apply fast discrete optimization techniques like graph cuts. Graph cuts is able to overcome the limitations of previously used active contour frameworks namely, large number of iterations, risk of being trapped in local minima, and sensitivity to initialization. The labels in the MRF formulation indicate joint occurrence of displacement vectors and segmentation class and the energy formulation is able to capture their mutual dependency. Experiments on real patient perfusion data and natural images show that JRS gives better performance than conventional registration and segmentation methods.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"283 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132445615","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: 26
Geometric averaging of X-ray signals in automatic exposure control 自动曝光控制中x射线信号的几何平均
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5649590
R. Snoeren, P. D. With
{"title":"Geometric averaging of X-ray signals in automatic exposure control","authors":"R. Snoeren, P. D. With","doi":"10.1109/ICIP.2010.5649590","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5649590","url":null,"abstract":"Improper dose control in X-ray cardio-vascular systems leads to a reduced Signal-to-Noise Ratio (SNR) in regions of interest of the X-ray image. We aim at reducing the influence of direct radiation, entering a measuring field for X-ray dose control in a Flat Detector which gives too bright areas (highlights) in the image. It is our desire to use a norm-like signal size that represents a minimal dose value while maximizing information transfer and thus image quality. In a dose control system, it is common practice to employ a special averaging technique for computing a representative signal level controlling the X-ray. We have found that the geometric averaging outperforms the existing techniques and significantly improves the image quality. Our approach reduces the highlight influence and guarantees an adequate Contrast-to-Noise ratio for decentered objects. We provide convincing experimental results showing a strongly improved image quality with respect to contrast and detail.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132574096","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 improved local feature descriptor via soft binning 通过软分组改进的局部特征描述符
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5653536
Feng Tang, Suk Hwan Lim, Nelson L. Chang
{"title":"An improved local feature descriptor via soft binning","authors":"Feng Tang, Suk Hwan Lim, Nelson L. Chang","doi":"10.1109/ICIP.2010.5653536","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5653536","url":null,"abstract":"We describe a robust feature descriptor called soft ordinal spatial intensity distribution (soft OSID) that is invariant to any monotonically increasing brightness changes. In traditional histogram-based feature descriptors, each pixel is explicitly assigned to a single histogram bin, making them not robust to image deformations and appearance changes. In this paper, we present a feature descriptor that is obtained by assigning each pixel to more than one bin where the fraction is determined by a weight function to put more weight on close bins. This makes the descriptor more robust to image changes like viewpoint changes, image blur, and JPEG compression. Extensive experiments show that the proposed descriptor significantly outperforms many state-of-the-art descriptors such as OSID, SIFT, GLOH, and PCA-SIFT under complex brightness changes. The proposed descriptor has far reaching implications for many applications in computer vision.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132703721","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
Mean shift based algorithm for mammographic breast mass detection 基于均值移位的乳腺肿块检测算法
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5652047
Farhang Sahba, A. Venetsanopoulos
{"title":"Mean shift based algorithm for mammographic breast mass detection","authors":"Farhang Sahba, A. Venetsanopoulos","doi":"10.1109/ICIP.2010.5652047","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5652047","url":null,"abstract":"This paper presents a novel scheme for mass detection in mammography images. In this method, a mean shift-based algorithm is used to cluster pixels in the image. The extraction of the breast border is the first step. Image pixels are then clustered using a mean shift algorithm that employs intensity information to extract a set of high density points in the feature space. This is followed by further stages involving mode fusion. Due to its non-parametric nature, mean shift algorithm can work effectively with non-convex regions resulting in better candidates for a reliable segmentation. The proposed method has been validated on standard datasets and the results show that this method can detect masses in mammography images, making it useful for breast cancer detection systems.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133110880","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: 8
A fully automated method of associating axial slices with a disc based on labeling of multi-protocol lumbar MRI 基于多协议腰椎MRI标记的轴向切片与椎间盘关联的全自动方法
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5652393
Jaehan Koh, V. Chaudhary, G. Dhillon
{"title":"A fully automated method of associating axial slices with a disc based on labeling of multi-protocol lumbar MRI","authors":"Jaehan Koh, V. Chaudhary, G. Dhillon","doi":"10.1109/ICIP.2010.5652393","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5652393","url":null,"abstract":"In a clinical setting, sagittal magnetic resonance imaging (MRI) slices along with axial MRI slices are commonly examined to diagnose lower lumbar disorders. Alongside, scan lines by projecting axial slices onto sagittal slices are provided to show the relationship about which axial slice is associated with a particular disc, resulting in better diagnosing disc-related disorders by a radiologist. In this paper, we propose a method to accurately associate an axial MRI with the particular intervertebral disc in a pre-labeled sagittal lumbar region MRI. A statistical distance prior from multi-protocol MR images of 68 patients is used in labeling process to accommodate the variability of the distance among patients of different ages and gender. Experiments with 93 patient data including 465 lumbar discs show that our method can assign the class membership to scan lines with over 92% accuracy.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133193328","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
Automatic production of personalized basketball video summaries from multi-sensored data 从多传感器数据中自动生成个性化篮球视频摘要
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5652750
Fan Chen, C. Vleeschouwer
{"title":"Automatic production of personalized basketball video summaries from multi-sensored data","authors":"Fan Chen, C. Vleeschouwer","doi":"10.1109/ICIP.2010.5652750","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5652750","url":null,"abstract":"We propose a flexible framework for producing highly personalized basketball video summaries, by intergrating contextural information, narrative user preferences on story pattern, and general production principles. Starting from the multiple streams captured by a distributed set of fixed cameras, we study the implementation of autonomous viewpoint determination and automatic temporal segment selection, and also discuss the production of visually comfortable output, by applying smoothing process to viewpoint selection and by defining efficient benefit functions to evaluate various summary organization. The efficiency of our framework is demonstrated by experimental results.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127810849","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
Detector-less ball localization using context and motion flow analysis 使用上下文和运动流分析的无检测器球定位
2010 IEEE International Conference on Image Processing Pub Date : 2010-12-03 DOI: 10.1109/ICIP.2010.5651147
F. Poiesi, F. Daniyal, A. Cavallaro
{"title":"Detector-less ball localization using context and motion flow analysis","authors":"F. Poiesi, F. Daniyal, A. Cavallaro","doi":"10.1109/ICIP.2010.5651147","DOIUrl":"https://doi.org/10.1109/ICIP.2010.5651147","url":null,"abstract":"We present a technique for estimating the location of the ball during a basketball game without using a detector. The technique is based on the analysis of the dynamics in the scene and allows us to overcome the challenges due to frequent occlusions of the ball and its similarity in appearance with the background. Based on the assumption that the ball is the point of focus of the game and that the motion flow of the players is dependent on its position during attack actions, the most probable candidates for the ball location are extracted from each frame. These candidates are then validated over time using a Kalman filter. Experimental results on a real basketball dataset show that the location of the ball can be estimated with an average accuracy of 82%.","PeriodicalId":228308,"journal":{"name":"2010 IEEE International Conference on Image Processing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134545302","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
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