Analytical shape determination of fiber-like objects with Virtual Image Correlation

TL;DR

This paper introduces the VIC method for accurately determining the shape, slope, and curvature of fiber-like objects from images, with low computational cost and high precision, even for complex shapes.

Contribution

It presents a novel analytical shape determination method using Virtual Image Correlation that improves accuracy and efficiency over existing techniques.

Findings

High precision in shape measurement demonstrated

Effective identification of complex fiber shapes with multiple loops

Low computational cost due to localized image analysis

Abstract

This paper reports a method allowing for the determination of the shape of deformed fiber-like objects. Compared to existing methods, it provides analytical results including the local slope and curvature which are of first importance, for instance, in beam mechanics. The presented VIC (Virtual Image Correlation) method consists in looking for the best correlation between the image of the fiber-like object and a virtual beam image, using an algorithm close to the Digital Image Correlation method developed in experimental solid mechanics. The computation only involves the part of the image in the vicinity of the fiber: the method is thus insensitive to the picture background and the computational cost remains low. Two examples are reported: the first proves the precision of the method, the second its ability to identify a complex shape with multiple loops.