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2017 14th International Conference on Computer Graphics, Imaging and Visualization最新文献

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Review of Computer Assisted Diagnosis to Analyze the MRI (Magnetic Resource Image) and Detect Alzheimer Disease 计算机辅助诊断分析阿尔茨海默病的研究进展
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-23 DOI: 10.1109/CGIV.2017.21
Amira Ben Rabeh, F. Benzarti, H. Amiri
{"title":"Review of Computer Assisted Diagnosis to Analyze the MRI (Magnetic Resource Image) and Detect Alzheimer Disease","authors":"Amira Ben Rabeh, F. Benzarti, H. Amiri","doi":"10.1109/CGIV.2017.21","DOIUrl":"https://doi.org/10.1109/CGIV.2017.21","url":null,"abstract":"Technological evolution has led to biomedical data acquisitions increasingly voluminous, heterogeneous and complex require efficient and timely systems to analyze and treatments to help physicians define diagnoses and appropriate prognoses in a timely manner. Support systems for Decision-making based on Biomedical Computing have become ubiquitous in clinical settings. In this context, we present in the first part of this article the main steps and components of a Computer-Assisted Diagnosis CAD system from the MRI (Magnetic Resonance Imaging) data. In the second part, we present some existing CAD systems to detect Alzheimer's disease (AD) at an early stage.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128385478","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
Cubic Trigonometric Bezier Spiral Curves 三次三角贝塞尔螺旋曲线
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.27
Md Yushalify Misro, A. Ramli, J. Ali, N. Hamid
{"title":"Cubic Trigonometric Bezier Spiral Curves","authors":"Md Yushalify Misro, A. Ramli, J. Ali, N. Hamid","doi":"10.1109/CGIV.2017.27","DOIUrl":"https://doi.org/10.1109/CGIV.2017.27","url":null,"abstract":"Shape parameters in trigonometric Bezier curves are very useful in providing flexibility to construct the desired curve. It helps users to find the best curve when dealing with designing and modelling tasks. It can simply be used without needing to change control points or using weightage in rational function. A technique for composing five templates of transition curves constructed by cubic trigonometric Bezier spiral is examined and presented.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121660831","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: 11
Automatic Face Recognition System Using Iso-Geodesic Curves in Riemanian Manifold 黎曼流形等测地线曲线自动人脸识别系统
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.25
Rachid Ahdid, K. Taifi, Said Said, M. Fakir, B. Manaut
{"title":"Automatic Face Recognition System Using Iso-Geodesic Curves in Riemanian Manifold","authors":"Rachid Ahdid, K. Taifi, Said Said, M. Fakir, B. Manaut","doi":"10.1109/CGIV.2017.25","DOIUrl":"https://doi.org/10.1109/CGIV.2017.25","url":null,"abstract":"In this paper, we present an automatic 3D face recognition system. This system is based on the representation of human faces surfaces as collections of Iso-Geodesic Curves (IGC) using 3D Fast Marching algorithm. To compare two facial surfaces, we compute a geodesic distance between a pair of facial curves using a Riemannian geometry. In the classifying step, we use: Neural Networks (NN), K-Nearest Neighbor (KNN) and Support Vector Machines (SVM). To test this method and evaluate its performance, a simulation series of experiments were performed on 3D Shape REtrieval Contest 2008 database (SHREC2008).","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132605600","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
Visual Scene Prediction for Blind People Based on Object Recognition 基于物体识别的盲人视觉场景预测
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.19
Hanen Jabnoun, F. Benzarti, H. Amiri
{"title":"Visual Scene Prediction for Blind People Based on Object Recognition","authors":"Hanen Jabnoun, F. Benzarti, H. Amiri","doi":"10.1109/CGIV.2017.19","DOIUrl":"https://doi.org/10.1109/CGIV.2017.19","url":null,"abstract":"Vision is one of the very essential human senses which is playing the most important role in human perception about surrounding environment. Hence, over the published papers on this subject, a variety of computer vision products and services are proposed by developing new methods for scene understanding. This work aims to introduce an approach that restores a central function of the visual system which is the visual scene interpretation. The proposed pipeline is based on the identification of surrounding objects in dissimilar frames from video scene. Otherwise, the experimental results using feature extractions showed good accuracy for detecting object in natural conditions. Features extraction and Bag of Visual Words correspondence are exploited for scene type understanding.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128420651","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
Diacritic Arabic Character Ontology 变音符阿拉伯字符本体
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.30
Houda Nakkach, H. Amiri
{"title":"Diacritic Arabic Character Ontology","authors":"Houda Nakkach, H. Amiri","doi":"10.1109/CGIV.2017.30","DOIUrl":"https://doi.org/10.1109/CGIV.2017.30","url":null,"abstract":"The main objective of our work is the online character recognition based on an ontology domain. So, this paper presents the creation of a CHAKEL-Onto ontology based on an expert in the domain. CHAKEL-Onto models the Arabic diacritical characters, presents 7 concepts, 36 spatial relations, 65 Rules of inference, 830 individuals. The CHAKEL-Onto is available for the purpose to improve On-tolgy research filed.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127221136","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
Designing for Game-based Learning Model: The Effective Integration of Flow Experience and Game Elements to Support Learning 基于游戏的学习模式设计:心流体验与游戏元素的有效整合以支持学习
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.31
Hussein Karam Hussein Abd Elsattar
{"title":"Designing for Game-based Learning Model: The Effective Integration of Flow Experience and Game Elements to Support Learning","authors":"Hussein Karam Hussein Abd Elsattar","doi":"10.1109/CGIV.2017.31","DOIUrl":"https://doi.org/10.1109/CGIV.2017.31","url":null,"abstract":"Game-based learning (GBL) is growing rapidly as a gaming industry as well as a field of academic research. Developing GBL is not an easy task. It requires a tight collaboration with domain experts and this need considering a complex mix of disciplines and technologies. Learning theory, learning contents, and game design are three multidisciplinary challenges involved in proper GBL development. This paper attempts to address these challenges by demonstrating how GBL can be conceptualized from different theoretical perspectives on learning and discuss a number of fundamental elements of game design that are essential for effective learning. Then, we propose a novel methodology of design and development of GBL model that facilitates the integration of flow experience with such game elements to support learning in games. Comparisons with existing frameworks are included. Evaluation and practical performance results supported by some case study called \"A day without computer-mediated technology\" are also demonstrated to verify the usability of the proposed model.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126508594","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
Tumor Detection in Mammography Images Using Fuzzy C-means and GLCM Texture Features 基于模糊c均值和GLCM纹理特征的乳腺x线影像肿瘤检测
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.22
M. M. Saleck, A. Elmoutaouakkil, M. Mouçouf
{"title":"Tumor Detection in Mammography Images Using Fuzzy C-means and GLCM Texture Features","authors":"M. M. Saleck, A. Elmoutaouakkil, M. Mouçouf","doi":"10.1109/CGIV.2017.22","DOIUrl":"https://doi.org/10.1109/CGIV.2017.22","url":null,"abstract":"The Fuzzy C-means (FCM) is one of the most efficient algorithms used in various studies which aims at segmenting the masses in mammogram images, thus to build a computer aided diagnosis (CAD) system capable of helping the physicians for an early diagnosis of the breast cancer. In this paper, we will introduce a new approach using FCM algorithm, in order to extract the mass from region-of-interested (ROI). The proposed method aims at avoiding problematic of the estimation of the cluster number in FCM by selecting as input data, the set of pixels which are able to provide us the information required to perform the mass segmentation by fixing two clusters only. The Gray Level Occurrence Matrix (GLCM) is used to extract the texture features for getting the optimal threshold, which separate between selected set and the other sets of the pixels that influences on the mass boundary accuracy. The performance of the proposed method is evaluated by specificity, sensitivity and accuracy. The results obtained from experimentations shows a good efficiency at the different measures used, in favor of our method.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124117039","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: 27
A Novel Selective Encryption DWT-Based Algorithm for Medical Images 一种新的基于dwt的医学图像选择性加密算法
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.10
M. Abdmouleh, A. Khalfallah, M. Bouhlel
{"title":"A Novel Selective Encryption DWT-Based Algorithm for Medical Images","authors":"M. Abdmouleh, A. Khalfallah, M. Bouhlel","doi":"10.1109/CGIV.2017.10","DOIUrl":"https://doi.org/10.1109/CGIV.2017.10","url":null,"abstract":"The remarkable development of the medical imagery is due to the large use of telecommunications and information technologies in the medical domain. However, since the telemedicine is a medical act that must answer to stern rules, and follow the easiness that is offered by the informatics sciences to violate the confidentiality and authenticity of medical data. To resolve this problem, a lot of methods combining compression and encryption have been developed in the literature to secure the transmission and the storage of medical images. In this paper, we propose a new approach of partial encryption based on the Discrete Wavelet Transform (DWT) and compatible with the norm JPEG2000 in order to assure an optimal and a secure transmission and storage of medical images. This approach is, on one hand, faster since it permits a very important gain in the encryption-decryption processing time (only 6.25% of the DWT matrix coefficients will be encrypted), and on the other hand more efficient because it permits to get an encrypted medical image.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114380602","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: 21
Dimensionality Reduction with Unsupervised Ensemble Learning Using K-Means Variants 基于k -均值变量的无监督集成学习降维
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.18
A. Filali, Chiraz Jlassi, N. Arous
{"title":"Dimensionality Reduction with Unsupervised Ensemble Learning Using K-Means Variants","authors":"A. Filali, Chiraz Jlassi, N. Arous","doi":"10.1109/CGIV.2017.18","DOIUrl":"https://doi.org/10.1109/CGIV.2017.18","url":null,"abstract":"Feature selection aims to diminish dimensionality for construct comprehensible learning models with good generalization performance. Feature selection methods are mostly studied independently according to the type of learning: supervised or unsupervised. This paper describes a novel feature selection algorithm for unsupervised clustering, that combines two clustering ensembles methods such as bagging and random subspace method using K-means variants to unlabeled data that estimates the out-of-bag feature importance from an ensemble of partitions. Every partition is constructed using a various bootstrap samples and a random subset of the features. The principal idea of the proposed unsupervised feature selection method is to search for a subset of all features such that the clustering algorithm trained on this feature subset can reach the most identical clustering solution to the one acquired by a set learning method. Experiments are performed on different known data sets for validating our proposed method. The results are promising and competitive with various representative algorithms.","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"153 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114619847","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 Breast Pectoral Muscle Segmentation on Digital Mammograms Using Morphological Watersheds 基于形态学分水岭的数字乳房x线照片胸肌自动分割
2017 14th International Conference on Computer Graphics, Imaging and Visualization Pub Date : 2017-05-01 DOI: 10.1109/CGIV.2017.24
K. Taifi, Rachid Ahdid, M. Fakir, A. Elbalaoui, Said Safi, Naima Taifi
{"title":"Automatic Breast Pectoral Muscle Segmentation on Digital Mammograms Using Morphological Watersheds","authors":"K. Taifi, Rachid Ahdid, M. Fakir, A. Elbalaoui, Said Safi, Naima Taifi","doi":"10.1109/CGIV.2017.24","DOIUrl":"https://doi.org/10.1109/CGIV.2017.24","url":null,"abstract":"The segmentation of mammograms plays a major role in isolating areas which can be subject of tumor. The identification of these zones is generally done in three steps: pectoral muscle segmentation, hard density zone detection and texture analysis of regions of interest. This paper deals with the segmentation of the pectoral muscle on a mammography image, in order to facilitate the work of experts while analyzing. The developed methodology is based on Morphological Watersheds. This algorithm has been tested on 80 digital mammography images of MIAS database. The performance is evaluated based upon the false positive (FP), false negative (FN) pixel percentage, and mean distance. All the average FN and FP pixel percentages are 3.68% and 2.98%, with the range shown from 0.90 to 0.99 for accuracy and 0.86 to 0.99 for precision rate. The method is also compared with three well-known pectoral muscle detection techniques and in most of the cases; it outperforms the other three approaches","PeriodicalId":269295,"journal":{"name":"2017 14th International Conference on Computer Graphics, Imaging and Visualization","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121415596","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
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