imagerExtra (version 1.3.2)

ThresholdML: Multilevel Thresholding

Description

Segments a grayscale image into several gray levels. Multilevel thresholding selection based on the artificial bee colony algorithm is used when thr is not a numeric vector. Preset parameters for fast computing is used when thr is "fast". Preset parameters for precise computing is used when thr is "precise". You can tune the parameters if thr is "manual". Also you can specify the values of thresholds by setting thr as a numeric vector.

Usage

ThresholdML(im, k, thr = "fast", sn = 30, mcn = 100, limit = 100,
  intervalnumber = 1000, returnvalue = FALSE)

Arguments

im

a grayscale image of class cimg

k

level of thresholding. k is ignored when thr is a numeric vector.

thr

thresholds, either numeric vector, or "fast", or "precise", or "manual".

sn

population size. sn is ignored except when thr is "manual".

mcn

maximum cycle number. mcn is ignored except when thr is "manual".

limit

abandonment criteria. limit is ignored except when thr is "manual".

intervalnumber

interval number of histogram. intervalnumber is ignored except when thr is "manual".

returnvalue

if returnvalue is TRUE, returns threshold values. if FALSE, returns a grayscale image of class cimg.

Value

a grayscale image of class cimg or a numeric vector

References

Ming-HuwiHorng (2011). Multilevel thresholding selection based on the artificial bee colony algorithm for image segmentation. Expert Systems with Applications.

Examples

# NOT RUN {
g <- grayscale(boats)
ThresholdML(g, k = 2) %>% plot
# }