A Labeled Array Distance Metric for Measuring Image Segmentation Quality
Berijanian, Maryam (Michigan State University)
Gensterblum, Katrina (Michigan State University)
Mutlu, Doruk Alp (Michigan State University)
Reagan, Katelyn (University of Wisconsin-Madison (USA))
Hart, Andrew (Michigan State University)
Colbry, Dirk (Michigan State University)

Data:	2024
Resum:	This work introduces two new distance metrics for comparing labeled arrays, which are common outputs of image segmentation algorithms. Each pixel in an image is assigned a label, with binary segmentation providing only two labels ('foreground' and 'background'). These can be represented by a simple binary matrix and compared using pixel differences. However, many segmentation algorithms output multiple regions in a labeled array. We propose two distance metrics, named LAD and MADLAD, that calculate the distance between two labeled images. By doing so, the accuracy of different image segmentation algorithms can be evaluated by measuring their outputs against a 'ground truth' labeling. Both proposed metrics, operating with a complexity of O(N) for images with N pixels, are designed to quickly identify similar labeled arrays, even when different labeling methods are used. Comparisons are made between images labeled manually and those labeled by segmentation algorithms. This evaluation is crucial when searching through a space of segmentation algorithms and their hyperparameters via a genetic algorithm to identify the optimal solution for automated segmentation, which is the goal in our lab, SEE-Insight. By measuring the distance from the ground truth, these metrics help determine which algorithm provides the most accurate segmentation.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Computer Vision ; Image Segmentation ; Manual Annotations ; Labeled Arrays ; Distance Metrics ; Fitness Function ; Genetic Algorithm
Publicat a:	ELCVIA, Vol. 23 Núm. 2 (2024) , p. 65-84 (Regular Issue) , ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.cat/article/view/1941
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/980000001027
DOI: 10.5565/rev/elcvia.1941

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