Automatic optimization of projection intensity for high dynamic range 3D surface measurement

被引:0
|
作者
Zheng, Renhao [1 ]
Li, Lijing [1 ]
Wan, Maosen [1 ]
Zhang, Wei [3 ]
Yu, Liandong [1 ,2 ]
机构
[1] Hefei Univ Technol HFUT, Sch Instrument Sci & Optoelect Engn, Hefei 230009, Peoples R China
[2] China Univ Petr UPC, Coll Control Sci & Engn, Qingdao 266580, Peoples R China
[3] Anhui Univ Finance & Econ, Dept Comp Technol & Sci, Bengbu 233030, Peoples R China
基金
中国国家自然科学基金;
关键词
High dynamic range; Multi threshold OTSU algorithm; Luminance; Phase shift method; OBJECTS;
D O I
10.1016/j.optlaseng.2023.107888
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Stripe projection profilers are widely used in many fields because of their high speed, high accuracy, and clear surface textures. In the structured light projection method, the complex reflectance distribution on the surface of the high-dynamic-range objective is an important factor that affects the measurement accuracy, as it can result in image over- and under-exposure. In this study, a method is proposed to adaptively determine the number of stripe patterns and the corresponding number of light intensities of the stripe patterns based on the complex reflectance of the surface of the object being measured. A multi threshold Otsu algorithm is used to classify the histogram of the surface reflectance distribution of the measured object, and several sets of stripe patterns with optimal light intensity are generated according to the light intensity response function. The original stripe patterns acquired at different light intensities are synthesized pixel by pixel into a high dynamic range (HDR) stripe image, and a four-step phase-shifting algorithm is used to obtain the unwrapped phase from the synthesized image. Experimental results show that this method can accurately measure the target of a surfacereflectance-transformed HDR.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] Intensity ratio approach for 3D profile measurement based on projection of triangular patterns
    Yang, Zongkai
    Wu, Ke
    Xi, Jiangtao
    Yu, Yanguang
    APPLIED OPTICS, 2014, 53 (02) : 200 - 207
  • [42] Phase correction method for dynamic 3D measurement based on fringe projection
    Zhou, Xingcan
    Li, Yong
    Huang, Kai
    Jiang, Yiteng
    OPTICAL METROLOGY AND INSPECTION FOR INDUSTRIAL APPLICATIONS VI, 2019, 11189
  • [43] A robust-coded pattern projection for dynamic 3D scene measurement
    Salvi, J
    Batlle, J
    Mouaddib, E
    PATTERN RECOGNITION LETTERS, 1998, 19 (11) : 1055 - 1065
  • [44] Measurement of 3D fundamental features by fusion of range, intensity and tactile images
    Umeda, K
    Kinoshita, G
    MFI2001: INTERNATIONAL CONFERENCE ON MULTISENSOR FUSION AND INTEGRATION FOR INTELLIGENT SYSTEMS, 2001, : 177 - 182
  • [45] Automatic gloss determination via optical 3D surface measurement
    Scherer, S.
    Danzi, R.
    Heirnii, F.
    Krenn, A.
    WOCHENBLATT FUR PAPIERFABRIKATION, 2007, 135 (21-22): : 1192 - 1195
  • [46] Physics-based supervised learning method for high dynamic range 3D measurement with high fidelity
    Li, Fuqian
    Niu, Xingman
    Zhang, Jing
    Zhang, Qican
    Wang, Yajun
    OPTICS LETTERS, 2024, 49 (03) : 602 - 605
  • [47] High-dynamic-range 3D measurement for E-beam fusion additive manufacturing based on SVM intelligent fringe projection system
    Liu, Yue
    Blunt, Liam
    Gao, Feng
    Jiang, Xiangqian
    SURFACE TOPOGRAPHY-METROLOGY AND PROPERTIES, 2021, 9 (03):
  • [48] Efficient 3D measurement of a HDR surface based on adaptive fringe projection
    Hu, Jialing
    Zhu, Jiangping
    Zhou, Pei
    APPLIED OPTICS, 2022, 61 (30) : 9028 - 9036
  • [49] Automatic and rapid whole-body 3D shape measurement based on multinode 3D sensing and speckle projection
    Guo, Jiping
    Peng, Xiang
    Li, Ameng
    Liu, Xiaoli
    Yu, Jiping
    APPLIED OPTICS, 2017, 56 (31) : 8759 - 8768
  • [50] 3D visualization of bronchiectases by minimum intensity projection
    Beier, J
    Bittner, RC
    Rohlfing, T
    Frank, W
    Wust, P
    Felix, R
    CAR '98 - COMPUTER ASSISTED RADIOLOGY AND SURGERY, 1998, 1165 : 176 - 181