Investigation and mapping strategy on influence of surface tilting in diffractive pattern correlation profilometry

Abstract

A new full-field profilometry based on diffraction image correlation (DIC) was developed in which the technique bases on calibrated database of reference diffractive images (RDIs) to estimate surface depth information. This technique has the advantage of removing vertical scanning for achieving high measurement efficiency in microscopic surface profilometry. However, as the diffractive images not only depend on the tested height but also the local surface tilt. Thus, the pre-built image database may not match the measured diffractive image and lead to a systematic measured error incurred by the surface tilting condition. Thus, in the article, the influence of surface tilt to the diffraction images is investigated and analyzed to understand the relationship between the surface tilt and the image variation. A lateral drifting phenomenon depends on the tilt angle and tilt direction was also quantified to estimate the impact of the tested surface height. Meanwhile, a detection algorithm to determine the center of diffractive image was developed to position the shifting quantity of the image. Moreover, the information coupling problem between height and tilting parameters, such as the tilt angle and tilt direction was studied to decouple these parameters from the tested height, so the tested surface can be reconstructed accurately. To realize the proposed method, some data processing strategies were also proposed to decouple the depth information from multi-surface parameters such as surface tilt angles (pitch and yaw) and direction effectively.