Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

A Self-Adaptive Multiple Exposure Image Fusion Method for High Reflective Surface Measurement

Version 1 : Received: 20 October 2022 / Approved: 26 October 2022 / Online: 26 October 2022 (10:13:48 CEST)

A peer-reviewed article of this Preprint also exists.

Chen, X.; Du, H.; Zhang, J.; Yang, X.; Xi, J. A Self-Adaptive Multiple Exposure Image Fusion Method for Highly Reflective Surface Measurements. Machines 2022, 10, 1004. Chen, X.; Du, H.; Zhang, J.; Yang, X.; Xi, J. A Self-Adaptive Multiple Exposure Image Fusion Method for Highly Reflective Surface Measurements. Machines 2022, 10, 1004.

Abstract

Fringe projection profilometry(FPP) has been extensively applied in various fields for its superior fast speed, high accuracy and high data density. However, measuring some objects with high reflective surfaces or high dynamic range surfaces remains challenging for FPP. Some multiple exposure image fusion methods have been proposed and successfully improved the measurement performance for these kinds of objects. Normally, these methods have a relatively fixed sequence of exposure settings determined by artificial experience or trial and error experiments, which may decrease the efficiency of the entire measurement process and may have less robustness to various environmental lighting conditions and object reflective properties. In this paper, a novel self-adaptive multiple exposure image fusion method is proposed with two main aspects of improvement on adaptively optimizing the initial exposure and the exposure sequence. By introducing the theory of information entropy, combined with the analysis of the characterization of fringe image entropy, an adaptive initial exposure searching method is first proposed. Then, an exposure sequence generation method based on dichotomy is further described. On the base of these two improvements, a novel self-adaptive multiple exposure image fusion method for FPP as well as its detailed procedures are given. Experimental results validate the performance of the proposed self-adaptivity multiple exposure image fusion method by measuring the objects with different surface reflectivity and in different ambient lighting conditions.

Keywords

Multiple exposure image fusion; Fringe projection profilometry; High reflective surface measurement

Subject

Engineering, Mechanical Engineering

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