Work

A Formal Evaluation of PSNR as Quality Measurement Parameter for Image Segmentation Algorithms

Year: 2016

Type: preprint

Abstract: Quality evaluation of image segmentation algorithms are still subject of debate and research. Currently, there is no generic metric that could be applied to any algorithm reliably. This article contains an evaluation for the PSRN (Peak Signal-To-Noise Ratio) as a metric which has been used to evaluate threshold level selection as well as the number of thresholds in the case of multi-level segmentation. The results obtained in this study suggest that the PSNR is not an adequate quality measurement for segmentation algorithms.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1605.07116

Authors: Fardo, Fernando A., Conforto, Victor H., de Oliveira, Francisco C., Rodrigues, Paulo S.

Institution: Centro Universitário FEI

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2398729036

Cites: 6

Cited by: 112

Related to: 10