计量学报2016，Vol.37Issue(5)：494-498,5.DOI:10.3969/j.issn.1000-1158.2016.05.09
彩色伪随机编码图像特征点神经网络匹配
Pseudo Random CoIor Encoded Image Feature Points Matching Based on NeuraI Network
摘要
Abstract
In order to study the theory of uncalibrated 3D euclidean reconstruction based on single image. An effective active-machine technique with structured light illumination is introduced which applies pseudo-random color code. Each interest point on scene surface can be identified exclusively according to the window property of pseudo-random array. It is found out that this active machine system can solve the correspondence between images in the passive machine system. Image recognition using neural networks can easily solve characteristic point match problem in coding structured light active vision system,the experiment is satisfactory.关键词
计量学/图像识别/主动视觉系统/伪随机编码/神经网络/特征点匹配/欧氏重构/不标定Key words
metrology/image recognition/active machine system/pseudo-random/neural network/correspondence between the camera images/euclidean reconstruction/uncalibration分类
通用工业技术引用本文复制引用
廖素引,吴博,卫敏,赵燕,李桂华,张梅..彩色伪随机编码图像特征点神经网络匹配[J].计量学报,2016,37(5):494-498,5.基金项目
国家自然科学基金（60931002，50275049）；安徽省自然科学研究项目（KJ2013A019）；安徽大学研究项目 （）
