A Formal Evaluation of PSNR as Quality Measurement Parameter for Image Segmentation Algorithms
Computer Vision and Pattern Recognition
2016-05-24 v1
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.
Keywords
Cite
@article{arxiv.1605.07116,
title = {A Formal Evaluation of PSNR as Quality Measurement Parameter for Image Segmentation Algorithms},
author = {Fernando A. Fardo and Victor H. Conforto and Francisco C. de Oliveira and Paulo S. Rodrigues},
journal= {arXiv preprint arXiv:1605.07116},
year = {2016}
}
Comments
11 pages, 8 figures