White Light Scanning Interferential Microscopy (WLSI) is a widely used technique for determining the 3D topography of surfaces with nanometer resolution. However, despite obtaining the topography with adequate resolution, the precise information of the object’s reflectance is lost due to a degrading of the microscopy images with interference fringes. These fringes make it challenging to obtain an extended focus image (EFI) to inspect details of the entire surface, as is done in standard microscopy. The typical procedure to estimate the reflected intensity of the object is to perform an averaging of the depth interference intensity signal. However, for many samples of the intensity signal, the effect of blurring becomes noticeable. Alternatively, in the case of few samples, remnant artifacts of the interference fringe patterns remain. In this work, we determine an adequate axial range that represents an optimal window for averaging and estimating the intensity of an EFI. A series of WLSI interference images were simulated, and EFI images were calculated by averaging over axial lengths normalized relative to the depth of field. Each EFI was compared with the reference image using the signal-to-noise ratio (SNR) and the universal quality index (UQI) metrics with the highest values obtained of 44.332 and 0.9997, respectively, for an axial range of 0.28DOF.
The implementation and generation of synthetic data for testing algorithms in optical metrology are often difficult to reproduce. In this work, we propose a framework for the generation of reproducible synthetic surface data. We present two study cases using the Code Ocean platform, which is based on Docker and Linux container technologies to turn source code repositories into executable images. i) We simulate interference pattern fringe images as acquired by a Michelson interferometric system. The reflectivity changes due to surface topography and roughness. ii) We simulate phase maps from rough isotropic surfaces. The phase data is simultaneously corrupted by noise and phase dislocations. This method relies on Gaussian-Laplacian pyramids to preserve surface features on different scales. The proposed framework enables reproducible surface data simulations, which could increase the impact of algorithm development in optical metrology.
KEYWORDS: Skin, Calibration, Cameras, 3D modeling, 3D metrology, Imaging systems, Fringe analysis, 3D image processing, Dermatology, Profilometers, 3D acquisition, 3D imaging metrology, Medical diagnostic instruments
The skin prick test (SPT) is the standard method for the diagnosis of allergies. It consists in placing an array of allergen drops on the skin of a patient, typically the volar forearm, and pricking them with a lancet to provoke a specific dermal reaction described as a wheal. The diagnosis is performed by measuring the diameter of the skin wheals, although wheals are not usually circular which leads to measurement inconsistencies. Moreover, the conventional approach is to measure their size with a ruler. This method has been proven prone to inter- and intra-observer variations. We have developed a 3D imaging system for the 3D reconstruction of the SPT. Here, we describe the proposed method for the automatic measurements of the wheals based on 3D data processing to yield reliable results. The method is based on a robust parametric fitting to the 3D data for obtaining the diameter directly. We evaluate the repeatability of the system under 3D reconstructions for different object poses. Although the system provides higher accuracy in the measurement, we compare the results to those produced by a physician.
The interferometric techniques of lateral shearing and white light scanning interferometry are combined to determine the variations of thickness of phase objects and the thickness of such objects is approximated through B-splines functions.
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