PROFILE EXTRACTION FOR OPTICAL LENS CURING PROCESS WITH IMAGE-BASED REGULARIZED TENSOR DECOMPOSITION

抄録

The stereolithography process has been invented to cure liquid acrylic resin into optical lenses with the designated profiles that deliver desired optical performance. Camera sensors are used online to collect a series of high-dimensional images, from which the profile of the optical lens can be extracted and characterized. The state-of-the-art computer vision and image processing methods fall short in effectively extracting the profile from the noisy image background. This paper presents a generic methodology that decomposes an in-process image into three components, i.e., background, profile, and noise, according to their variant pixel intensities. Such intensity variance is the result of the difference between the refractive index of the cured optical lens and that of the surrounding curable resin. The physical properties of individual image components are explicitly formulated in a regularized tensor decomposition model and represented by the mathematical properties of the corresponding tensor components. An ADMM-based algorithm is developed to optimally estimate the model parameters and accurately extract the profile component. The advantages of the proposed method are demonstrated by a real-world case study.