Foot anthropometry device and single object image thresholding

TL;DR

This paper presents a device and algorithm for foot anthropometry that uses a single image for measurement, outperforming traditional thresholding methods especially in poor lighting conditions, with accuracy comparable to manual methods.

Contribution

A novel foot measurement device and image processing algorithm that improves accuracy and robustness in varying lighting conditions, validated against manual measurements.

Findings

Average underfoot measurement error was 4mm compared to manual.

Mean absolute error for underfoot length was 1.6mm.

No significant difference between manual and image-based measurements.

Abstract

This paper introduces a device, algorithm and graphical user interface to obtain anthropometric measurements of foot. Presented device facilitates obtaining scale of image and image processing by taking one image from side foot and underfoot simultaneously. Introduced image processing algorithm minimizes a noise criterion, which is suitable for object detection in single object images and outperforms famous image thresholding methods when lighting condition is poor. Performance of image-based method is compared to manual method. Image-based measurements of underfoot in average was 4mm less than actual measures. Mean absolute error of underfoot length was 1.6mm, however length obtained from side foot had 4.4mm mean absolute error. Furthermore, based on t-test and f-test results, no significant difference between manual and image-based anthropometry observed. In order to maintain anthropometry process performance in different situations user interface designed for handling changes in light conditions and altering speed of the algorithm.