mia-2dstack-cmeans-presegment {-i io} {-o string} {-L int} [
options
...]
This program first evaluates a sparse histogram of an input image series, then runs a c-means classification over the histogram, and then estimates the mask for one (given) class based on class probabilities. This program accepts only images of eight or 16 bit integer pixels.
input image(s) to be filtered. For supported file types see Plugin type: 2dimage/io
Save probability map to this file
output file name type
output file name base
verbosity of output, print messages of given level and higher priorities. Supported priorities starting at lowest level are:
| debug: | Debug output |
| message: | Normal messages |
| info: | Low level messages |
| error: | Report errors |
| fatal: | Report only fatal errors |
| trace: | Function call trace |
| warning: | Warnings |
| fail: | Report test failures |
print copyright information
print this help
print a short help
print the version number and exit
Percent of the extrem parts of the histogram to be collapsed into the respective last histogram bin.
C-means class initializer. For supported plug-ins see Plugin type: 1d/cmeans
Probability threshold value to consider a pixel as seed pixel.
Class label to create the mask from
Maxiumum number of threads to use for processing,This number should be lower or equal to the number of logical processor cores in the machine. (-1: automatic estimation).
Run the program over images imageXXXX.png with the sparse histogram, threshold the lower 30% bins (if available), run cmeans with two classes on the non-zero pixels and then create the mask for class 1 as foregroundXXXX.png.
mia-2dstack-cmeans-presegment -i imageXXXX.png -o foreground -t png --histogram-tresh=30 --classes 2 --label 1
Gert Wollny