by Klette, R and Žunić, J
Abstract:
This paper informs about number-theoretical and geometrical estimates of worst-case bounds for quantization errors in calculating features such as moments, moment based features, or perimeters in image analysis, and about probability-theoretical estimates of error bounds (e.g. standard deviations) for such digital approximations. New estimates (with proofs) and a review of previously known results are provided.
Reference:
Multigrid convergence of calculated features in image analysis (Klette, R and Žunić, J), In Journal of Mathematical Imaging and Vision, Kluwer Academic Publishers, volume 13, 2000.
Bibtex Entry:
@article{klette2000multigridanalysis,
author = "Klette, R and Žunić, J",
journal = "Journal of Mathematical Imaging and Vision",
month = "Dec",
pages = "173--191",
publisher = "Kluwer Academic Publishers",
title = "Multigrid convergence of calculated features in image analysis",
volume = "13",
year = "2000",
abstract = "This paper informs about number-theoretical and geometrical estimates of worst-case bounds for quantization errors in calculating features such as moments, moment based features, or perimeters in image analysis, and about probability-theoretical estimates of error bounds (e.g. standard deviations) for such digital approximations. New estimates (with proofs) and a review of previously known results are provided.",
doi = "10.1023/A:1011289414377",
issn = "0924-9907",
issue = "3",
language = "eng",
}