[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.3807/COPP.2020.4.5.411

Three-dimensional Shape Recovery from Image Focus Using Polynomial Regression Analysis in Optical Microscopy

Lee, Sung-An (Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology)
Lee, Byung-Geun (Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology)

Publication Information

Current Optics and Photonics / v.4, no.5, 2020 , pp. 411-420 More about this Journal

Abstract

Non-contact three-dimensional (3D) measuring technology is used to identify defects in miniature products, such as optics, polymers, and semiconductors. Hence, this technology has garnered significant attention in computer vision research. In this paper, we focus on shape from focus (SFF), which is an optical passive method for 3D shape recovery. In existing SFF techniques using interpolation, all datasets of the focus volume are approximated using one model. However, these methods cannot demonstrate how a predefined model fits all image points of an object. Moreover, it is not reasonable to explain various shapes of datasets using one model. Furthermore, if noise is present in the dataset, an error will be generated. Therefore, we propose an algorithm based on polynomial regression analysis to address these disadvantages. Our experimental results indicate that the proposed method is more accurate than existing methods.

Keywords

Shape from focus; Approximation techniques; Curve fitting; Polynomial regression analysis;

Citations & Related Records

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