startweb.area: Opens default web browser and loads a web page for area...
In LeArEst: Border and Area Estimation of Data Measured with Additive Error

Function startweb.area() opens a web browser and loads the page for area estimation of object shown in a picture. Use this function if you can isolate a part of the picture with uniformly distributed dots on an elliptical domain with unclear borders. Sequence of actions on the web page is as follows:

Load a picture in JPG format
Click on upper left and lower right corner of a rectangle surrounding observed object so the rectangle is drawn
Set data and estimation parameters
Click on Estimate

1	startweb.area()

The area estimation algorithm takes many horizontal and vertical (if "horizontal + vertical" slicing is selected) or star-shaped (if "star" slicing is selected) slices of the object. Length estimation procedure is conducted on each slice and in that way set of edge points is obtained. Lastly, ellipse or circle is fitted on that set of points by function EllipseDirectFit or CircleFitByPratt from the package conicfit and area of that ellipse or circle is returned as the result. The area is measured in pixels, as well as percentage of the whole image.

Parameters that can be set on the web page are as follows:

Data parameters

Levels of grey: Number of colors (shades of grey) used in analysis.
Box size: The algorithm takes each pixel of a picture and maps it to box_size * box_size matrix. It is done in a way that the brightness of the observed pixel dictates the quantity of dots in mentioned matrix. Distribution of dots in matrix is uniform. Ultimately, length estimation is done on the set of the resulting matrices.
Line thickness: Width of the slice, i.e. the maximum length between surrounding pixel and the drawn line so that pixel is to be taken into account for length estimation. All surrounding pixels are orthogonally projected on the central line.
Number of slices: Number of slices after cutting in one direction. Defaults to 10. Slices are equally thick in both directions. Smaller number of cuts will be automatically applied for smaller dimension if the chosen rectangle is not a square.
Slicing: Sets slicing method for the edge point estimation. Can be "horizontal + vertical" or "star".
Parallelization: Sets whether to distribute area estimation on multiple CPU cores. If set to On, total number of cores - 1 are used.
Object brightness: Sets whether observed object is bright or dark.
Represent object as: Represent estimated object as an ellipse or as a circle.

Estimation parameters

Error distribution: Type of the error distribution. Can be Gauss, Laplace, T1, T2, T3, T4 or T5 (Student).
Error standard deviation: Estimation method for the error standard deviation. Can be Maximum Likelihood (ML) or the Method of Moments. If one does not want to estimate the deviation but to explicitly enter it, he should choose "Enter value" and enter the deviation in the lower field.

In order to have quadratic pixels on the screen, please use proportional screen resolution. In the case of modern LCD (LED) displays, these are usually native screen resolutions. If your display has aspect ratio width:height = 16:9, these resolutions are 1280x720, 1600x900, 1920x1080, etc. In the case od 16:10 display, use 1280x800, 1440x900, 1920x1200, etc. If you use nonproportional screen resolution, pixels on the screen will not be quadratic, so estimated values measured in pixels may not be correct.