Global shape reconstruction of nano grid with singly fixed camera

查看全文 作　　者：WEI [1]YangJie;WU [2]ChengDong;DONG [3]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)》索引2011年第54卷第4期,共9页

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：纳米操纵相机参数格形模糊成像视觉传感器重建方法参数变化纳米尺度

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Global shape reconstruction of nano grid with singly fixed camera

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