Global shape reconstruction of nano grid with singly fixed camera  

作　　者：WEI YangJie WU ChengDong DONG ZaiLi 

机构地区：[1]Graduate School of Chinese Academy of Sciences & the State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China [2]School of Information Science & Engineering,Northeast University,Shenyang 110004,China [3]State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China

出　　处：《Science China(Technological Sciences)》2011年第4期1044-1052,共9页中国科学（技术科学英文版）

基　　金：supported by the CAS FEA international partnership program for creative research teams

摘　　要：Depth from defocus(DFD),as a typical shape reconstruction method,has been widely researched in most recent years.However,all the existing DFD algorithms require at least two defocused images with different camera parameters.Unfortunately,in micro/nano manipulation,any change on visual sensor's parameters is absolutely forbidden.Therefore,a novel DFD method to reconstruct the shape of a nano grid on micro/nano scale is researched in this paper.First,the blurring imaging model is constructed with the relative blurring and the diffusion equation.Second,the relationship between depth and blurring is discussed from four aspects.Subsequently,depth measurement problem is transformed into an optimization issue which is solved using the gradient flow algorithm.Finally,experiment results and error analysis are conducted to show the feasibility and effectiveness of the proposed method.

关 键 词：depth from defocus diffusion equation shape reconstruction nano grid 

分 类 号：TB383[一般工业技术—材料科学与工程] TB852.1