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Qian Kemao

Researcher at Nanyang Technological University

Publications -  118
Citations -  4811

Qian Kemao is an academic researcher from Nanyang Technological University. The author has contributed to research in topics: Fourier transform & Phase (waves). The author has an hindex of 30, co-authored 114 publications receiving 3680 citations. Previous affiliations of Qian Kemao include University of Science and Technology of China.

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Two-dimensional windowed Fourier transform for fringe pattern analysis: Principles, applications and implementations

TL;DR: Two algorithms, one based on filtering and the other based on similarity measure, are developed and some applications based on these two algorithms are explored, including strain determination, phase unwrapping, phase-shifter calibration, fault detection, edge detection and fringe segmentation.
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Windowed Fourier transform for fringe pattern analysis

TL;DR: Two approaches are developed on the extraction of phase and phase derivatives from either phase-shifted fringe patterns or a single carrier fringe pattern based on the best match between the fringe pattern and computer-generated windowed exponential elements.
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Phase error analysis and compensation for nonsinusoidal waveforms in phase-shifting digital fringe projection profilometry

TL;DR: A novel and simple iterative phase compensation algorithm is proposed to compensate the nonsinusoidal phase error and experiments show that the proposed algorithm can be used for effective phase error compensation in practical phase-shifting FPP.
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Comparison of Fourier transform, windowed Fourier transform, and wavelet transform methods for phase extraction from a single fringe pattern in fringe projection profilometry

TL;DR: Phase extraction methods from a single fringe pattern using different transform methods are compared using both simulations and experiments to determine the merits and limitations of each.
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Quality-guided phase unwrapping technique: comparison of quality maps and guiding strategies

TL;DR: A detailed comparison of classical, two-section, and stack-chain guiding strategies are chosen for comparison and the classical guiding strategy with a data structure of indexed interwoven linked list is the one to use.