Wei Hao, Li Hongru, Li Xuan, Wang Sha, Deng Guoliang, Zhou Shouhuan
College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China.
CISDI Information Technology Co., Ltd., Chongqing 401122, China.
Sensors (Basel). 2025 Mar 20;25(6):1942. doi: 10.3390/s25061942.
Fringe projection profilometry (FPP) is a widely employed technique owing to its rapid speed and high accuracy. However, when FPP is utilized to measure shiny surfaces, the fringes tend to be saturated or too dark, which significantly compromises the accuracy of the 3D measurement. To overcome this challenge, this paper proposes an efficient method for the 3D measurement of shiny surfaces based on FPP. Firstly, polarizers are employed to alleviate fringe saturation by leveraging the polarization property of specular reflection. Although polarizers reduce fringe intensity, a deep learning method is utilized to enhance the quality of fringes, especially in low-contrast regions, thereby improving measurement accuracy. Furthermore, to accelerate measurement efficiency, a dual-frequency complementary decoding method is introduced, requiring only two auxiliary fringes for accurate fringe order determination, thereby achieving high-efficiency and high-dynamic-range 3D measurement. The effectiveness and feasibility of the proposed method are validated through a series of experimental results.
条纹投影轮廓术(FPP)因其速度快、精度高而被广泛应用。然而,当使用FPP测量光亮表面时,条纹往往会饱和或过暗,这严重影响了三维测量的精度。为了克服这一挑战,本文提出了一种基于FPP的光亮表面三维测量有效方法。首先,利用偏振器通过利用镜面反射的偏振特性来减轻条纹饱和。虽然偏振器会降低条纹强度,但利用深度学习方法来提高条纹质量,特别是在低对比度区域,从而提高测量精度。此外,为了提高测量效率,引入了双频互补解码方法,仅需两个辅助条纹即可准确确定条纹级数,从而实现高效、高动态范围的三维测量。通过一系列实验结果验证了该方法的有效性和可行性。