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2008 XXI Brazilian Symposium on Computer Graphics and Image Processing最新文献

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Diffusion Tensor Imaging Segmentation by Watershed Transform on Tensorial Morphological Gradient 基于张量形态梯度的分水岭变换扩散张量成像分割
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.17
L. Rittner, R. Lotufo
{"title":"Diffusion Tensor Imaging Segmentation by Watershed Transform on Tensorial Morphological Gradient","authors":"L. Rittner, R. Lotufo","doi":"10.1109/SIBGRAPI.2008.17","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.17","url":null,"abstract":"While scalar image segmentation has been studied extensively, diffusion tensor imaging (DTI) segmentation is a relatively new and challenging task. Either existent segmentation methods have to be adapted to deal with tensorial information or completely new segmentation methods have to be developed to accomplish this task. Alternatively, what this work proposes is the computation of a tensorial morphological gradient of DTI, and its segmentation by IFT-based watershed transform. The strength of the proposed segmentation method is its simplicity and robustness, consequences of the tensorial morphological gradient computation. It enables the use, not only of well known algorithms and tools from the mathematical morphology, but also of any other segmentation method to segment DTI, since the computation of the tensorial morphological gradient transforms tensorial images in scalar ones. In order to validate the proposed method, synthetic diffusion tensor fields were generated, and Gaussian noise was added to them. A set of real DTI was also used in the method validation. All segmentation results confirmed that the proposed method is capable to segment different diffusion tensor images, including noisy and real ones.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116402663","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: 15
Estimating the Skew Angle of Scanned Document through Background Area Information 利用背景区域信息估计扫描文档的倾斜角
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.34
Angélica A. Mascaro, George D. C. Cavalcanti
{"title":"Estimating the Skew Angle of Scanned Document through Background Area Information","authors":"Angélica A. Mascaro, George D. C. Cavalcanti","doi":"10.1109/SIBGRAPI.2008.34","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.34","url":null,"abstract":"The skew correction of scanned document images is an important step toward an automatic recognition system. Several techniques have been developed to estimate the skew angle of a scanned document. However, most of these techniques have the problem of expensive computational costs. A variation of a fast method based on parallelograms covering is presented in this article. The objective is to obtain lower computation time and provide a way to work well over noisy images and also over different layouts containing non-text areas with no decrease in performance. Experimental study with different databases achieved results that overcome previous techniques.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117167722","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: 4
Multidimensional Visualization to Support Analysis of Image Collections 支持图像集合分析的多维可视化
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.30
D. M. Eler, Marcel Y. Nakazaki, F. Paulovich, D. P. Santos, Maria Cristina Ferreira de Oliveira, J. B. Neto, R. Minghim
{"title":"Multidimensional Visualization to Support Analysis of Image Collections","authors":"D. M. Eler, Marcel Y. Nakazaki, F. Paulovich, D. P. Santos, Maria Cristina Ferreira de Oliveira, J. B. Neto, R. Minghim","doi":"10.1109/SIBGRAPI.2008.30","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.30","url":null,"abstract":"Multidimensional visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces a methodology and a software tool called PEx-Image - Projection Explorer for Image for analysis and exploration of image collections employing visualizations. The visual mappings proposed here are similarity-based multidimensional projections and point placements, which layout the data on a plane for visual exploration. The proposed approach supports various image analysis tasks such as feature selection and classification, improving data exploration capabilities. We also illustrate how it can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114396931","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
Structural Matching of 2D Electrophoresis Gels using Graph Models 基于图模型的二维电泳凝胶结构匹配
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.14
A. Noma, Á. Pardo, R. M. C. Junior
{"title":"Structural Matching of 2D Electrophoresis Gels using Graph Models","authors":"A. Noma, Á. Pardo, R. M. C. Junior","doi":"10.1109/SIBGRAPI.2008.14","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.14","url":null,"abstract":"2D electrophoresis is a well known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation and the goal is to perform a differential analysis between pairs of images to study changes in protein content. It is thus necessary to register two images by finding spot correspondences. Although it may seem a simple task, generally, the manual processing of this kind of images is very cumbersome. The complete task of individual spot matching and gel registration is a complex and time consuming process when strong variations between corresponding sets of spots are expected. Besides, because an one-to-one mapping is expected between the two images, missing spots there may exist on both images (i.e. spots without correspondence). In order to solve this problem, this paper proposes a new distance together with a correspondence estimation algorithm based on graph matching which takes into account the structural information between the detected spots. Each image is represented by a graph and the task is to find an isomorphism between subgraphs. Successful experimental results using real data are presented, including a comparative performance evaluation.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130144184","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: 4
Benchmark for Quantitative Evaluation of Assisted Object Segmentation Methods to Image Sequences 图像序列辅助目标分割方法的定量评价基准
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.22
F. C. Flores, R. Lotufo
{"title":"Benchmark for Quantitative Evaluation of Assisted Object Segmentation Methods to Image Sequences","authors":"F. C. Flores, R. Lotufo","doi":"10.1109/SIBGRAPI.2008.22","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.22","url":null,"abstract":"Evaluation of segmentation methods applied to image sequences consists in the analysis of such methods according to quantitative and/or qualitative criteria, usually driven to some application. Literature proposes several metrics for quantitative evaluation of object segmentation methods to image sequences, but it is still considered an open problem, since no one of the proposed metrics is considered the standard one. More, as the best of our knowledge, there is no method in literature that does computational quantitative evaluation of assisted methods to object segmentation in image sequence. This paper introduces a benchmark to do such quantitative evaluation. This evaluation is done according to several criteria such as the robustness of segmentation and the easiness to segment the objects through the sequence. Experimental results also evaluates the robustness of the watershed from propagated markers technique.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"409 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123636373","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
Bayesian Estimation of Hyperparameters in MRI through the Maximum Evidence Method 基于最大证据法的MRI超参数贝叶斯估计
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.5
D. E. Oliva, R. Isoardi, G. Mato
{"title":"Bayesian Estimation of Hyperparameters in MRI through the Maximum Evidence Method","authors":"D. E. Oliva, R. Isoardi, G. Mato","doi":"10.1109/SIBGRAPI.2008.5","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.5","url":null,"abstract":"Bayesian inference methods are commonly applied to the classification of brain magnetic resonance images (MRI). We use the maximum evidence (ME) approach to estimate the most probable parameters and hyperparameters for models that take into account discrete classes (DM) and models accounting for the partial volume effect (PVM). An approximate algorithm was developed for model optimization, since the exact image inference calculation is computationally expensive. The method was validated using simulated images and a digital phantom. We show that the evidence is a very useful figure for error prediction, which is to be maximized respect to the hyperparameters. Additionally, it provides a tool to determine the most probable model given measured data.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129511160","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
Using Multi-agent Systems for Sampling and Rendering Implicit Surfaces 使用多智能体系统进行隐式曲面的采样和绘制
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.18
P. Jepp, J. Denzinger, B. Wyvill, M. Sousa
{"title":"Using Multi-agent Systems for Sampling and Rendering Implicit Surfaces","authors":"P. Jepp, J. Denzinger, B. Wyvill, M. Sousa","doi":"10.1109/SIBGRAPI.2008.18","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.18","url":null,"abstract":"In this paper a multi-agent system for sampling and rendering implicit surfaces is presented (MASSRIS). Previous approaches to pen-and-ink style renderings of implicit surfaces were based on particle systems, which, for a complex surface, are slow to achieve a good distribution of particles and subsequently to trace features. The method proposed in this research extends traditional particles into semi-autonomous agents that sample the implicit model and illustrate surface features. Agents use goal directed behaviors to achieve a good coverage of surface strokes and feature outline identification faster than with previous particle-based methods.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124251876","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
A New Training Algorithm for Pattern Recognition Technique Based on Straight Line Segments 一种基于直线段的模式识别训练算法
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.35
J. Ribeiro, R. F. Hashimoto
{"title":"A New Training Algorithm for Pattern Recognition Technique Based on Straight Line Segments","authors":"J. Ribeiro, R. F. Hashimoto","doi":"10.1109/SIBGRAPI.2008.35","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.35","url":null,"abstract":"Recently, a new pattern recognition technique based on straight line segments (SLSs) was presented. The key issue in this new technique is to find a function based on distances between points and two sets of SLSs that minimizes a certain error or risk criterion. An algorithm for solving this optimization problem is called training algorithm. Although this technique seems to be very promising, the first presented training algorithm is based on a heuristic. In fact, the search for this best function is a hard nonlinear optimization problem. In this paper, we present a new and improved training algorithm for the SLS technique based on gradient descent optimization method. We have applied this new training algorithm to artificial and public data sets and their results confirm the improvement of this methodology.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126476902","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: 4
Efficient Text Color Modulation for Printed Side Communications and Data Hiding 用于印刷侧通信和数据隐藏的有效文本颜色调制
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.23
P. Borges, E. Izquierdo, J. Mayer
{"title":"Efficient Text Color Modulation for Printed Side Communications and Data Hiding","authors":"P. Borges, E. Izquierdo, J. Mayer","doi":"10.1109/SIBGRAPI.2008.23","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.23","url":null,"abstract":"This paper improves the use of text color modulation (TCM) as a reliable text document data hiding method. Using TCM, the characters in a document have their color components modified (possibly unperceptually) according to a side message to be embedded. This work presents a detection metric and an analysis determining the detection error rate in TCM, considering an assumed print and scan (PS) channel model. In addition, a perceptual impact model is employed to evaluate the perceptual difference between a modified and a non-modified character. Combining this perceptual model and the results from the detection error analysis it is possible to determine the optimum color modulation values. The proposed detection metric also exploits the orientation characteristics of color halftoning to reduce the error rate. In particular, because color halftoning algorithms use different screen orientation angles for each color channel, this is used as an effective feature to detect the embedded message. Experiments illustrate the validity of the analysis and the applicability of the method.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132451126","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
Crop Type Recognition Based on Hidden Markov Models of Plant Phenology 基于植物物候隐马尔可夫模型的作物类型识别
2008 XXI Brazilian Symposium on Computer Graphics and Image Processing Pub Date : 2008-10-12 DOI: 10.1109/SIBGRAPI.2008.26
Paula Beatriz Cerqueira Leite, R. Feitosa, A. Formaggio, G. Costa, K. Pakzad, I. Sanches
{"title":"Crop Type Recognition Based on Hidden Markov Models of Plant Phenology","authors":"Paula Beatriz Cerqueira Leite, R. Feitosa, A. Formaggio, G. Costa, K. Pakzad, I. Sanches","doi":"10.1109/SIBGRAPI.2008.26","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2008.26","url":null,"abstract":"This work introduces a hidden Markov model (HMM) based technique to classify agricultural crops. The method recognizes different crops by analyzing their spectral profiles over a sequence of satellite images. Different HMMs, one for each of the considered crop classes, are used to relate the varying spectral response along the crop cycles with plant phenology. The method assigns for a given image segment the crop class whose corresponding HMM presents the highest probability of emitting the observed sequence of spectral values. Experiments were conducted upon a sequence of 12 previously classified LANDSAT images. The performance of the proposed multitemporal classification method was compared to that of a monotemporal maximum likelihood classifier, and the results indicated a remarkable superiority of the HMM-based method, which achieved an average of no less than 93% accuracy in the identification of the correct crop, for sequences of data containing a single crop class.","PeriodicalId":330622,"journal":{"name":"2008 XXI Brazilian Symposium on Computer Graphics and Image Processing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131578195","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
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