首页 | 本学科首页   官方微博 | 高级检索  
     

基于模糊判别的立体匹配算法
引用本文:周东翔,蔡宣平,孙茂印.基于模糊判别的立体匹配算法[J].中国图象图形学报,2001,6(4):359-364.
作者姓名:周东翔  蔡宣平  孙茂印
作者单位:[1]国防科技大学电子科学与工程学院,长沙410073 [2]国防科技大学电子科学与工程学院,长沙4
摘    要:立体视觉一直是计算机视觉领域所研究的一个中心问题,而立体匹配则是立体视觉技术中最关键也是最困难的部分,就得到适用于基于图象绘制技术中视图合成的准确、高密度视差图(Disparity Map)而言,现有的一些方法存在一定的局限性。考虑到立体匹配过程中存在的不确定性和模糊性,本文将已获得广泛应用的模糊理论引入立体匹配领域,提出了基于模糊判别的立体匹配算法,并用实际图象与合成图象进行了实验验证,结果表明该算法效果良好,具有实用价值。

关 键 词:计算机视觉  模糊判别  立体匹配  视差图  立体匹配算法  计算机图形学
文章编号:1006-8961(2001)04-0359-06
修稿时间:2000年4月14日

A Stereo Matching Algorithm Based on Fuzzy Identification
ZHOU Dong-xiang,CAI Xuan-ping and SUN Mao-yin.A Stereo Matching Algorithm Based on Fuzzy Identification[J].Journal of Image and Graphics,2001,6(4):359-364.
Authors:ZHOU Dong-xiang  CAI Xuan-ping and SUN Mao-yin
Abstract:Stereo vision has long been one of the central research problems in computer vision, and stereo matching is the most important and difficulty issue of stereo vision. There are some limits for existing approaches to recover precise and dense disparity map. Feature-based stereo can produce more precise matching but only sparse disparity map. On the other hand, Area-based approaches can provide dense disparity map but less precise matching. In the situation of image synthesis for IBR, we need not only precise matching but also a dense disparity map. Thinking of the uncertain and fuzzy characteristic during matching, we introduce the widely used fuzzy set theory to the field of stereo matching, and propose an algorithm based on fuzzy identification. The algorithm uses the information of gradient magnitudes, angles of orientation and gray value information of nearby points as the identification facts. Experiments with real and synthetic images have been performed, they show that this algorithm is effective and it is of great value to use.
Keywords:Computer vision  Fuzzy identification  Stereo matching  Disparity map
本文献已被 CNKI 维普 等数据库收录!
点击此处可从《中国图象图形学报》浏览原始摘要信息
点击此处可从《中国图象图形学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号