R: Suggests threshold levels to use in binarizing an image...

autoThreshold {rtiff} | R Documentation

## Suggests threshold levels to use in binarizing an image channel.

### Description

This is an implementation of the Ridler method for binarization (see references). NOTE: The order of the values returned did not match what is described in the "value" section below. This is fixed in this version.

### Usage

    autoThreshold(d.m, est = 0.5)

### Arguments

`d.m` | A data matrix representing the pixel intensities for a single image channel (e.g. readTiff("image.tif")@red).
`est` | The initial thresholding estimate to work from. The default only works if the pixel intensities are between 0 and 1, otherwise the mean intensity of the entire channel is likely a reasonable starting point. The selection of the estimate should not influence the final threshold selected.

### Value

A vector (v) of estimates, the 3rd element of which is the true Ridler estimate. However, experience demonstrates that sometimes a lower (elements 1 or 2) or higher (elements 4 or 5) estimate performs better for a given application. The Ridler estimate is the mean between the average intensity of bright regions in the raster and the average intensity of dim regions. This is v[3]. v[1] is the average of dim regions, v[5] is the average of dim regions, and v[2] and v[4] are the mean between the Ridler estimate and v[1] and v[2], respectively.

### Author(s)

Eric Kort <eric.kort@vai.org>

### References

Ridler T, Calvard S. Picture thresholding using an iterative selection method. IEEE Trans on Systems Man and Cybernetics, SMC 8;630-2.

### Examples

    tif <- readTiff(system.file("tiff", "jello.tif", package="rtiff"))
    threshold <- autoThreshold(tif@red)
    plot(tif)
    plot(tif@red > threshold[3])

[Package rtiff version 1.4.6 Index]