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2009 Digital Image Computing: Techniques and Applications最新文献

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Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data 多元偏态混合模型:荧光活化细胞分选数据的应用
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.88
Kui Wang, S. Ng, G. McLachlan
{"title":"Multivariate Skew t Mixture Models: Applications to Fluorescence-Activated Cell Sorting Data","authors":"Kui Wang, S. Ng, G. McLachlan","doi":"10.1109/DICTA.2009.88","DOIUrl":"https://doi.org/10.1109/DICTA.2009.88","url":null,"abstract":"In many applied problems in the context of pattern recognition, the data often involve highly asymmetric observations. Normal mixture models tend to overfit when additional components are included to capture the skewness of the data. Increased number of pseudo-components could lead to difficulties and inefficiencies in computations. Also, the contours of the fitted mixture components may be distorted. In this paper, we propose to adopt mixtures of multivariate skew t distributions to handle highly asymmetric data. The EM algorithm is used to compute the maximum likelihood estimates of model parameters. The method is illustrated using a flurorescence-activated cell sorting data.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129756757","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: 60
Exploiting Bayesian Belief Network for Adaptive IP-Reuse Decision 基于贝叶斯信念网络的自适应ip复用决策
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.21
A. Azman, A. Bigdeli, M. Biglari-Abhari, Yasir Mohd-Mustafah, B. Lovell
{"title":"Exploiting Bayesian Belief Network for Adaptive IP-Reuse Decision","authors":"A. Azman, A. Bigdeli, M. Biglari-Abhari, Yasir Mohd-Mustafah, B. Lovell","doi":"10.1109/DICTA.2009.21","DOIUrl":"https://doi.org/10.1109/DICTA.2009.21","url":null,"abstract":"A smart camera processor has to perform substantial amount of processing of data-intensive operations. Hence, it is vital to identify critical segments of the processing load by involving HW/SW codesign in smart camera system design. This paper presents a novel fully automatic hybrid framework that combines heuristic and knowledge-based approaches to partition, allocate and schedule IP modules efficiently. In this work, the concept of Bayesian Belief Network (BBN) is utilised and incorporated into the proposed framework. In the experiment section of this paper, we report a comparison of our proposed framework with three previously published work: A BBN based method proposed by a research group from the University of Arizona, the exhaustive algorithm and finally the with greedy algorithms.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116353568","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
Object Modelling in Videos via Multidimensional Features of Colours and Textures 通过颜色和纹理的多维特征在视频中的对象建模
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.32
Zhuhan Jiang
{"title":"Object Modelling in Videos via Multidimensional Features of Colours and Textures","authors":"Zhuhan Jiang","doi":"10.1109/DICTA.2009.32","DOIUrl":"https://doi.org/10.1109/DICTA.2009.32","url":null,"abstract":"We propose to model a tracked object in a video sequence by locating a list of object features that are ranked according to their ability to differentiate against the image background. The Bayesian inference is utilised to derive the probabilistic location of the object in the current frame, with the prior being approximated from the pervious frame and the posterior achieved via the current pixel distribution of the object. The experiment of the proposed method on the video sequences has also been conducted and has shown its effectiveness in capturing the target in a moving background and with non-rigid object motion.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127236393","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
Shape Signature for Retinal Biometrics 视网膜生物识别的形状签名
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.69
M. C. Azemin, D. Kumar, H. Wu
{"title":"Shape Signature for Retinal Biometrics","authors":"M. C. Azemin, D. Kumar, H. Wu","doi":"10.1109/DICTA.2009.69","DOIUrl":"https://doi.org/10.1109/DICTA.2009.69","url":null,"abstract":"The technique used in the only commercially available system for retinal biometrics is based on encoding the vessel structure surrounding the optic disc. However, it has been reported that this technique has low inter-personal variability, making it unsuitable for identifying an individual from a large database. In this paper we propose a new technique based on the shape signature to quantify the contours of the retina structure to increase the inter-personal distance and to lessen the effects of growth of new blood vessels around the optic disc. Correlations are computed as a measure of similarity of 1560 unique retina pairings between different eye images. The results are obtained from a modified shape signature technique of quantifying the contour of the retina structure particularly for the branch-like vessels. The distribution of the correlation, which range from -0.54 to 0.76, resembles a normal distribution with a mean of 0.09. Effects against translation, rotation, scaling and noise are also investigated.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131979448","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: 12
Patch Contour Matching by Correlating Fourier Descriptors 基于相关傅立叶描述子的斑块轮廓匹配
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.17
F. Larsson, M. Felsberg, Per-Erik Forssén
{"title":"Patch Contour Matching by Correlating Fourier Descriptors","authors":"F. Larsson, M. Felsberg, Per-Erik Forssén","doi":"10.1109/DICTA.2009.17","DOIUrl":"https://doi.org/10.1109/DICTA.2009.17","url":null,"abstract":"Fourier descriptors (FDs) is a classical but still popular method for contour matching. The key idea is to apply the Fourier transform to a periodic representation of the contour, which results in a shape descriptor in the frequency domain. Fourier descriptors have mostly been used to compare object silhouettes and object contours; we instead use this well established machinery to describe local regions to be used in an object recognition framework. We extract local regions using the Maximally Stable Extremal Regions (MSER) detector and represent the external contour by FDs. Many approaches to matching FDs are based on the magnitude of each FD component, thus ignoring the information contained in the phase. Keeping the phase information requires us to take into account the global rotation of the contour and shifting of the contour samples. We show that the sum-of-squared differences of FDs can be computed without explicitly de-rotating the contours. We compare our correlation based matching against affine-invariant Fourier descriptors (AFDs) and demonstrate that our correlation based approach outperforms AFDs on real world data.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125636747","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
Feature Extraction from Contours Shape for Tumor Analyzing in Mammographic Images 基于轮廓形状的特征提取用于乳房x线图像的肿瘤分析
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.71
Atef Boujelben, A. Chaabani, Hedi Tmar, M. Abid
{"title":"Feature Extraction from Contours Shape for Tumor Analyzing in Mammographic Images","authors":"Atef Boujelben, A. Chaabani, Hedi Tmar, M. Abid","doi":"10.1109/DICTA.2009.71","DOIUrl":"https://doi.org/10.1109/DICTA.2009.71","url":null,"abstract":"The cancer treatment is effective only if it is detected at an early stage. In this context, Mammography is the most efficient method for early detection. Due to the complexity of this last, the distinction of microcalcifications or opacities is very difficult. This paper deals with the problem of shape feature extraction in digital mammograms, particularly the boundary information. In fact, we evaluated the efficiency on boundary information possessed by mass region. We propose feature vector based in boundary analysis in ameliorating three points of view like RDM, convexity and angular features. We use the Digital Database for Screening Mammography “DDSM” for experiments. Some classifiers as Multilayer Perception “MLP” and k-Nearest Neighbours “kNN” are used to distinguish the pathological records from the healthy ones. Using “MLP” classifiers we obtained 94,2% as sensitivity (percentage of pathological ROIs correctly classified). The results in term of specificity (percentage of non-pathological ROIs correctly classified) grows around 97,9% using MLP classifier.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132939730","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: 16
A Clustering Based Automated Glacier Segmentation Scheme Using Digital Elevation Model 基于聚类的数字高程模型冰川自动分割方案
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.53
S. Z. Gilani, N. I. Rao
{"title":"A Clustering Based Automated Glacier Segmentation Scheme Using Digital Elevation Model","authors":"S. Z. Gilani, N. I. Rao","doi":"10.1109/DICTA.2009.53","DOIUrl":"https://doi.org/10.1109/DICTA.2009.53","url":null,"abstract":"We present an automated scheme for segmentation of high mountain glaciers using Fast Adaptive Medoid Shift (FAMS) algorithm and Digital Elevation Model (DEM). FAMS is a non-parametric clustering technique that has been optimized and made data driven from its original Medoid Shift algorithm. 6 Band TM sensor satellite images are fed to FAMS as input along with height, slope and gradient information extracted from a DEM. Clean glacier and debris covered glacier are treated separately. Each glacier having its own regional minima and debris is delineated individually. A unique slope-gradient model is used to separate the debris covered portion from its surrounding and extension rocks as well as to exclude the lateral moraine. The proposed model is independent of the DN values of satellite image bands and therefore is able to perform well even in areas where debris covered glaciers exactly resemble the surrounding rocks. Experiments have been carried out on KaraKoram and Hindukush mountain ranges of Asia and validated against supervised manual segmentation results as well as Google EarthTM imagery. Results have shown our fully automated method to be time efficient, robust and accurate.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132251568","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
Self-Organizing Map Methodology and Google Maps Services for Geographical Epidemiology Mapping 用于地理流行病学制图的自组织地图方法论和谷歌地图服务
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.46
Jingyuan Zhang, Hao Shi, Yanchun Zhang
{"title":"Self-Organizing Map Methodology and Google Maps Services for Geographical Epidemiology Mapping","authors":"Jingyuan Zhang, Hao Shi, Yanchun Zhang","doi":"10.1109/DICTA.2009.46","DOIUrl":"https://doi.org/10.1109/DICTA.2009.46","url":null,"abstract":"The Health Geographical Information System (GIS) has been used in many organizations for the management and visualization of public health data. As epidemiology information has become a part of health data repository in the health data management system, many health researchers have dedicated their research areas to geographical epidemiology information analysis and visualization. The Population Health Epidemiology Unit of the Department of Health and Human Services (DHHS) in Tasmania uses the web-based epidemiology system (‘WebEpi’) to conduct monitoring and surveillance of the health of Tasmanian population. In this paper, the epidemiology data Self-Organizing Map (SOM) analysis methodology and Google Maps services techniques of WebEpi are presented. SOM has been used as a tool to recognize patterns with data sets measuring epidemiology data and related geographical information. Google Maps services offer Web GIS Application Programming Interface (API) and GIS views. The integration of SOM and Google Maps facilitates the epidemiology data pattern recognition and geo-visualization which enables health research to be conducted in a novel and effective way.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130532240","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
Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors 基于统计分析和霍夫变换的机载激光雷达强度数据分类及其在电力线走廊中的应用
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.83
Yuee Liu, Zhengrong Li, R. Hayward, R. Walker, Hang Jin
{"title":"Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors","authors":"Yuee Liu, Zhengrong Li, R. Hayward, R. Walker, Hang Jin","doi":"10.1109/DICTA.2009.83","DOIUrl":"https://doi.org/10.1109/DICTA.2009.83","url":null,"abstract":"Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115427300","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: 63
SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images 从不相关中筛选相关:自动检测训练图像中的目标
2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.59
E. Zhang, M. Mayo
{"title":"SIFTing the Relevant from the Irrelevant: Automatically Detecting Objects in Training Images","authors":"E. Zhang, M. Mayo","doi":"10.1109/DICTA.2009.59","DOIUrl":"https://doi.org/10.1109/DICTA.2009.59","url":null,"abstract":"Many state-of-the-art object recognition systems rely on identifying the location of objects in images, in order to better learn its visual attributes. In this paper, we propose four simple yet powerful hybrid ROI detection methods (combining both local and global features), based on frequently occurring keypoints. We show that our methods demonstrate competitive performance in two different types of datasets, the Caltech101 dataset and the GRAZ-02 dataset, where the pairs of keypoint bounding box method achieved the best accuracies overall.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123898450","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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