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  • Open Access


    Phase Error Compensation of Three-Dimensional Reconstruction Combined with Hilbert Transform

    Tao Zhang1,*, Jie Shen1, Shaoen Wu2

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3121-3131, 2021, DOI:10.32604/cmc.2021.016362

    Abstract Nonlinear response is an important factor affecting the accuracy of three-dimensional image measurement based on the fringe structured light method. A phase compensation algorithm combined with a Hilbert transform is proposed to reduce the phase error caused by the nonlinear response of a digital projector in the three-dimensional measurement system of fringe structured light. According to the analysis of the influence of Gamma distortion on the phase calculation, the algorithm establishes the relationship model between phase error and harmonic coefficient, introduces phase shift to the signal, and keeps the signal amplitude constant while filtering out… More >

  • Open Access


    Three-Dimensional Measurement Using Structured Light Based on Deep Learning

    Tao Zhang1,*, Jinxing Niu1, Shuo Liu1, Taotao Pan1, Brij B. Gupta2,3

    Computer Systems Science and Engineering, Vol.36, No.1, pp. 271-280, 2021, DOI:10.32604/csse.2021.014181

    Abstract Three-dimensional (3D) reconstruction using structured light projection has the characteristics of non-contact, high precision, easy operation, and strong real-time performance. However, for actual measurement, projection modulated images are disturbed by electronic noise or other interference, which reduces the precision of the measurement system. To solve this problem, a 3D measurement algorithm of structured light based on deep learning is proposed. The end-to-end multi-convolution neural network model is designed to separately extract the coarse- and fine-layer features of a 3D image. The point-cloud model is obtained by nonlinear regression. The weighting coefficient loss function is introduced More >

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