标题: 以边缘侦测为基础的高效率强健式视讯物件分割技术
An Efficient and Robust Edge-based Video Object Segmentation Method
作者: 李德渊
林进灯
Chin-Teng Lin
电控工程研究所
关键字: 初始背景建立;视讯物件分割;边缘运算器;改变侦测;物件追踪;揭开背景;Initial background construction;Video object segmentation;Edge operator;Change detection;Object tracking;Uncovered background
公开日期: 2003
摘要: 本论文提出一个新的视讯物件分割演算法。这个视讯物件分割演算法可区分为两部分:初始背景的建立与物件的追踪。在第一个部分,我们根据些许连续的影像建立出可信赖的初始背景,并且使用改善过的相连元件法(Modified Connected Component Method)将一张物件影像分割成许多相同灰阶的区块。然后,利用边缘运算器找出物件的移动边缘,再依照此资讯找出揭开背景(Uncovered Background)的区块,最后更新初始背景。而在第二个部分,我们使用背景资讯和边缘运算器追踪新物件的边缘,并透过改变侦测和背景预测的方法移除揭开背景的边缘,进而抽取出完整的视讯物件。实验证明利用背景资讯和边缘资讯,我们可以有效地分割出精确的物件并且改善以往只用改变侦测(Change detection)作为视讯物件分割的缺点。
In this thesis, we propose a new video object segmentation algorithm. The video object segmentation algorithm consists of two major parts: initial background construction and object tracking. In the first part, we construct the reliable initial background in several consecutive frames and use modified connected component to partition an object image into many blobs with similar luminance. Then, we use edge operator to find the moving edge and use it to find the uncovered background blob. Finally, the initial background frame could be updated. In secondary part, we use background information and edge operator to find the moving edge of the object. Then, the uncovered background edge is removed by using the change detection method and background predictive method. Further, the perfect video object could be extracted. According to the experimental results, the proposed method combining background information and edge information can greatly improve the performance of precise object segmentation compared with the conventional change detection approaches.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT009112534
http://hdl.handle.net/11536/44879
显示于类别:Thesis


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