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A full-field chromatic confocal microscopy (CCM) using a multispectral sensor was developed for quasi-one-shot microscopic 3D surface measurement. An innovative optical configuration employs a digital micromirror device (DMD) and a multispectral sensor is used to realize CCM with full-field area scanning. In the optical design, an area-scan type chromatic dispersive objective is specially designed to achieve measuring specification. Based on a self-developed chromatic dispersive objective, the FOV for one shot measurement can be reached to 1.8×1.3 mm2 which is immersive to microscopic profilometry. The spectral image captured by the multispectral sensor at each pinhole position has a unique spectrum pattern corresponding to its conjugate measured depth. A normalized cross-correlation (NCC) algorithm is developed to establish a spectrum-depth response curve with its corresponding spectrum pattern sets for accurate reconstruction of the tested 3D surface profile. With real test on standard targets, the measurement repeatability for a single surface depth is less than 0.6 μm.

A single-exposure microscopic profilometry using artificial neural network (ANN) was developed for 3-D profile reconstruction of precise surface geometry. Optical profilometry is an important technique widely applied in many fields. However, in addition to optical aberration of the microscope itself, tilting of a local testing surface can affect the direction of the reflected light, thus causing undesired measurement errors. To overcome these problems, various methods or optical strategies have been developed, but most of them suffer from undue measurement errors attributed to the local surface gradient formed by the measured point and its neighboring surface geometry. This study proposed a novel method that combined diffractive image microscopy (DIM) with ANN. To train the ANN model, diffractive images of various surface orientations were collected for learning the complex mapping relationships between diffractive images and their corresponding surface orientations. The proposed method could simultaneously measure the height, tilting angle and tilting direction of a local surface. 3-D surface reconstruction by the proposed method required no prior knowledge of neighboring geometric information adjacent to the measured point. Using the developed approach achieved a surface height repeatability of 0.257 μm and a surface inclined angle repeatability of 0.037°, evidencing the realization of precise 3-D microscopic profilometry.

This work presents a novel microscopic profilometry using diffraction image correlation, which is appropriate for in-situ automated optical inspection (AOI). In contrast to the traditional confocal microscopy, the developed technique replaces the detector pinhole by observing and matching the diffraction patterns. Thus accurate surface depth detection can be achieved by eliminating time-consuming vertical scanning operation. The development is the first attempt in optics to use image correlation between the pre-calibrated database of diffraction images and the measured one of the detecting object surface. The feasibility of the method has been theoretically verified by scalar diffraction theory, then verified by experimental testing. Also, a depth response curve with the physical meaning of similarity is introduced and interpreted. Meanwhile, multi-point lateral scanning in one field of view (FOV) is achieved by quickly switching micromirrors on the digital micromirror device (DMD), thus the quasi full-field 3-D reconstruction can be acquired by combining tens of captured images. Verified experimentally, a 3-D reconstruction with sub-micrometer vertical resolution can be realized, with a tunable lateral resolution.

A full-field microprofilometry involving innovative image correlation was developed for profile measurement without vertical scanning. High-speed optical inspection has become critical for confirming precise dimensions in semiconductor fabrication such as microbumping in 3D stacked ICs and precision manufacturing. A digital micromirror device (DMD) is designed to serve as a point-light-source array in a quasiconfocal optical configuration and perform lateral scanning to minimize signal crosstalk between neighboring testing points. More importantly, multiple diffractive images are detected and measured with a prebuilt depth-correlated database to extract the height information of a tested surface. A 100-nm repeatability can be realized in the absence of a detector pinhole and without vertical scanning, thus achieving high-speed submicrometer-scale surface profilometry.