2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)最新文献_第6页

Modeling of 2D Objects with Weighted-Quadratic Trigonometric Spline 二维物体的加权二次三角样条建模

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.15

M. Sarfraz, Shamaila Samreen, M. Hussain

引用次数: 9

Abnormal Events Detection Based on Trajectory Clustering 基于轨迹聚类的异常事件检测

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.65

Najla Bouarada Ghrab, Emna Fendri, Mohamed Hammami

引用次数: 11

Automatic Bifurcation Detection in Coronary X-Ray Angiographies 冠状动脉x线造影中的自动分岔检测

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.70

Asma Kerkeni, A. Ben Abdallah, A. Manzanera, M. H. Bedoui

引用次数: 1

Grouping K-Means Adjacent Regions for Semantic Image Annotation Using Bayesian Networks 基于贝叶斯网络的k -均值分组相邻区域语义图像标注

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.54

M. Oujaoura, R. El Ayachi, B. Minaoui, M. Fakir, O. Bencharef

引用次数: 2

Classification and Recognition of Dental Images Using a Decisional Tree 基于决策树的牙齿图像分类与识别

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.82

Hicham Riri, A. Elmoutaouakkil, A. Beni-Hssane, Farid Bourezgui

引用次数: 9

On Performance Evaluation of Registration Algorithms for 3D Point Clouds 三维点云配准算法的性能评价

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.18

Mouna Attia, Y. Slama, M. Kamoun

引用次数: 16

Markovian Segmentation of Color and Gray Level Images 彩色和灰度图像的马尔可夫分割

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.57

M. Ameur, N. Idrissi, C. Daoui

引用次数: 4

A Combined Approach Based on Fuzzy Classification and Contextual Region Growing to Image Segmentation 基于模糊分类和上下文区域增长的图像分割方法

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.41

Mahaman Sani Chaibou, Karim Kalti, Soulaiman Bassel, M. Mahjoub

{"title":"A Combined Approach Based on Fuzzy Classification and Contextual Region Growing to Image Segmentation","authors":"Mahaman Sani Chaibou, Karim Kalti, Soulaiman Bassel, M. Mahjoub","doi":"10.1109/CGIV.2016.41","DOIUrl":"https://doi.org/10.1109/CGIV.2016.41","url":null,"abstract":"We present in this paper an image segmentation approach that combines a fuzzy semantic region classification and a context based region-growing. Input image is first over-segmented. Then, prior domain knowledge is used to perform a fuzzy classification of these regions to provide a fuzzy semantic labeling. This allows the proposed approach to operate at high level instead of using low-level features and consequently to remedy to the problem of the semantic gap. Each oversegmented region is represented by a vector giving its corresponding membership degrees to the different thematic labels and the whole image is therefore represented by a Regions Partition Matrix. The segmentation is achieved on this matrix instead of the image pixels through two main phases: focusing and propagation. The focusing aims at selecting seeds regions from which information propagation will be performed. The propagation phase allows to spread toward others regions and using fuzzy contextual information the needed knowledge ensuring the semantic segmentation. An application of the proposed approach on mammograms shows promising results.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124380271","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

O-LEACH of Routing Protocol for Wireless Sensor Networks 无线传感器网络路由协议的O-LEACH

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.84

Wassim Jerbi, Abderrahmen Guermazi, H. Trabelsi

{"title":"O-LEACH of Routing Protocol for Wireless Sensor Networks","authors":"Wassim Jerbi, Abderrahmen Guermazi, H. Trabelsi","doi":"10.1109/CGIV.2016.84","DOIUrl":"https://doi.org/10.1109/CGIV.2016.84","url":null,"abstract":"LEACH protocol called Low Energy Adaptive Clustering Hierarchy, is a protocol that allows the formation of distributed cluster. In each cluster, LEACH randomly selects some sensor nodes called cluster heads (CHs). The selection of CHs is made with a probabilistic calculation. It is supposed that each non-CH node joins a cluster and becomes a cluster member. Nevertheless, some CHs can be concentrated in a specific part of the network. Thus several sensor nodes cannot reach any CH. to solve this problem. We created an O-LEACH Orphan nodes protocol, its role is to reduce the sensor nodes which do not belong the cluster. O-LEACH present two scenarios, the first scenario consists, a cluster member will be able to play the role of a gateway which allows the joining of orphan nodes. The gateway node has to connect a number of orphan nodes, thus the gateway node is considered as a CH' for connected orphans. As a result, orphan nodes become able to send their data messages to the CH' which performs in turn data aggregation and send aggregated data message to the CH. The second scenario consists, if in an area not covered, the number of orphan nodes is very important, if number of cluster member is superior to number of orphan nodes, a sub-cluster will be created. The first orphan node reached the gateway (member of cluster) will be a CH'. O-Leach enables the formation of a new method of cluster, leads to a long life and minimal energy consumption. In orphan node possess enough energy and seeks to be covered by the network. The principal novel contribution of the proposed work is O-LEACH protocol which provides coverage of the whole network with a minimum number of orphaned nodes and has a very high connectivity rates. The simulation results show that O-LEACH performs better than LEACH in terms of coverage, connectivity rate, energy and scalability.","PeriodicalId":351561,"journal":{"name":"2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125218003","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: 54

Image Authentication Based on Faber Schauder DWT 基于Faber Schauder DWT的图像认证

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV) Pub Date : 2016-03-01 DOI: 10.1109/CGIV.2016.24

Assma Azeroual, K. Afdel

引用次数: 0