Surface reconstruction based on the camera relative irradiance
Author(s) -
Bin Yao,
Weifang Sun,
Binqiang Chen,
Tianxiang Zhou,
Xincheng Cao
Publication year - 2018
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1177/1550147718759566
Subject(s) - computer science , irradiance , computer vision , calibration , process (computing) , measure (data warehouse) , surface reconstruction , artificial intelligence , approximation error , optics , surface (topology) , object (grammar) , observational error , charge coupled device , algorithm , mathematics , physics , geometry , statistics , database , operating system
Precise three-dimensional measurements of surfaces are significant in many fields. Usually, three-dimensional descriptions of the object surface have to be acquired by contact measure probe or other non-contact equipment. The paper proposed a novel surface reconstruction method that uses camera relative irradiance via the image gray-scale value information under fixed ring light. After calibrations of the measurement condition, just one image of the object is necessary to reconstruct the surface. The method mainly involves two aspects: the calibration process and the surface reconstruction process. The purpose of the calibration process is to find the relation between the image gray-scale value and the relative irradiance of the charge-coupled device sensor in different expose conditions. The surface reconstruction mainly focuses on the relation between the irradiance and height information. The experiment result shows the relative error of the illumination measurement result obtained using charge-coupled device camera is less than 2.91%. Reconstruction error is mainly result from the truncation error of algorithm calculation. An example is presented to verify the performance of this technique. The reconstruction experiments demonstrated that it can successfully measure the geometrical characteristics from the specified view of the object.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom