Statistics, Department of

The R Journal
Date of this Version
12-2017
Document Type
Article
Citation
The R Journal (December 2017) 9(2); Editor: Roger Bivand
Abstract
This paper describes an R package LeArEst that can be used for estimating object dimensions from a noisy image. The package is based on a simple parametric model for data that are drawn from uniform distribution contaminated by an additive error. Our package is able to estimate the length of the object of interest on a given straight line that intersects it, as well as to estimate the object area when it is elliptically shaped. The input data may be a numerical vector or an image in JPEG format. In this paper, background statistical models and methods for the package are summarized, and the algorithms and key functions implemented are described. Also, examples that demonstrate its usage are provided.
Included in
Numerical Analysis and Scientific Computing Commons, Programming Languages and Compilers Commons
Comments
Copyright 2017, The R Foundation. Open access material. License: CC BY 4.0