Efficient One-to-One Pair Matching for 2-D and 3-D Edge Detection Evaluation

Samuel Smith, Ian Williams

2020

Abstract

This paper introduces a novel efficient method of obtaining one to one correspondence matching for fast, accurate, performance evaluation of edge detectors. The proposed Efficient Pairing Strategy (EPS) overcomes the computational cost limitations of the Hungarian algorithm, enabling a fast and accurate evaluation of 3-D data and large 2-D data sets. In this work, the accuracy of the EPS method is measured against the optimal Hungarian method across a data set of 124240 images, and is shown to produce accurate results with a Pearson Pairwise Correlation coefficient of 0.99 . Additionally the efficiency of the EPS method is compared against the fast Closest Distance Match (CDM), the Cost Scaling Assignment (CSA), and the commonly applied Pratt figure of Merit (PFOM) methods. Analysis shows the EPS and CSA methods both produce cost scaling accuracy comparable to the Hungarian algorithm. However the EPS method outperforms the CSA method in computational efficiency, achieving linear computation time comparable to the efficient sub-optimal methods. More generally, we make recommendations for using one to one correspondence matching over other methods in order to produce reliable performance scores across 2-D and 3-D image data.

Paper Citation

in Harvard Style

Smith S. and Williams I. (2020). Efficient One-to-One Pair Matching for 2-D and 3-D Edge Detection Evaluation. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 590-598. DOI: 10.5220/0009330005900598

in Bibtex Style

@conference{visapp20,
author={Samuel Smith and Ian Williams},
title={Efficient One-to-One Pair Matching for 2-D and 3-D Edge Detection Evaluation},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={590-598},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009330005900598},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Efficient One-to-One Pair Matching for 2-D and 3-D Edge Detection Evaluation
SN - 978-989-758-402-2
AU - Smith S.
AU - Williams I.
PY - 2020
SP - 590
EP - 598
DO - 10.5220/0009330005900598
PB - SciTePress