Abstract
Digital image correlation (DIC)-based stereo 3D shape measurement is a kind of single-shot method, which can achieve high precision and is robust to vibration as well as environment noise. The efficiency of DIC has been greatly improved with the proposal of inverse compositional Gauss-Newton (IC-GN) operators for both first-order and second-order warp functions. Without the algorithm itself, both the registration accuracy and efficiency of DIC-based stereo matching for shapes with different complexities are closely related to the selection of warp function, subset size, and convergence criteria. Understanding the similarity and difference of the impacts of prescribed subset size and convergence criteria on first-order and second-order warp functions, and how to choose a proper warp function and set optimal subset size as well as convergence criteria for different shapes are fundamental problems in realizing efficient and accurate 3D shape measurement. In this work, we present a comparative analysis of first-order and second-order warp functions for DIC-based 3D shape measurement using IC-GN algorithm. The effects of subset size and convergence criteria of first-order and second-order warp functions on the accuracy and efficiency of DIC are comparatively examined with both simulation tests and real experiments. Reference standards for the selection of warp function for different kinds of 3D shape measurement and the setting of proper convergence criteria are recommended. The effects of subset size on the measuring precision using different warp functions are also concluded.
Highlights
Optical 3D shape measurement has become one of the research hotspots in the field of measurement due to the advantages of high precision, non-contact, and high speed, etc
We present a comparative analysis of first-order and second-order warp functions for digital image correlation (DIC)-based 3D shape measurement using inverse compositional Gauss-Newton (IC-GN) algorithm
SU and RMSEU of ROI1&2 measured by IC-GN2 under the convergence threshold of 0.1 are smaller than that measured by IC-GN1 under any one of the tested convergence thresholds
Summary
Optical 3D shape measurement has become one of the research hotspots in the field of measurement due to the advantages of high precision, non-contact, and high speed, etc. The forward additive Newton-Raphson (FA-NR) algorithm is a typical iterative updating method, which is widely used with first-order [11,12] and second-order [13,14] warp functions in last decade. Almost all the researches related to DIC adopted IC-GN algorithm for sub-pixel registration, which can be summed up as first-order and second-order IC-GN. As far as we know, there is no comparative analysis about the measurement effectiveness and different characteristics of first-order and second-order warp functions until now. It is hard to select a proper warp function and set optimal parameters according to the characteristics of different measurements. We present a comparative analysis of first-order and second-order warp functions for DIC-based 3D shape measurement using IC-GN algorithm. The remainder of this paper is organized as follows: The principle of DIC-based single-shot
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