thresMlComCur
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Name
thresMlComCur - multi-level thresholding by Reddi using
complexity curve
Syntax
thresMlComCur [-mean] [-med] [-scale <scale>]
[-nt <nt>] <inimage> [<outimage>]
Description
thresMlComCur performs multi-level thresholding
according to the method of Reddi et al., here applying
complexity curve instead of histogram (see ref).
Options
-
-mean
- Output is mean of pixels between two thresholds.
-
-med
- Output is median of pixels between two thresholds.
-
-scale
- Output is threshold-level * scale. EX: pixels
between 3rd and 4th threshold get value 3*scale.
If scale is too large, it is adjusted down to make 255
the maximum output value. Default scale is too large.
-
-nt no_of_ths
- Desired number of thresholds.
Use onlu one of -mean, -med and -scale.
See also
thresMl(1), thresMlAppScale(3), thresMlAppMean(3),
thresMlAppMedian(3), thresMlApply(3), histoCentroid(3),
thresMlCentroid(3), thresMlCentroid(3), mkComCur(3),
thresMlComCur(3), thresMlReddi(3), thresMlReddi(1),
thresMlWaHa(3), thresMlWaHa(1)
Restrictions
inimage must have bands with pixel type unsigned byte.
1 <= thresholds <= 255.
Reference
-
S. S. Reddi, S. F. Rudin and H. R. Keshavan
- "An Optimal Multiple Threshold Scheme for Image Segmentation"
IEEE Transactions on Systems, Man and Cybernetics,
Vol SMC-14, pp 661-665, 1984.
-
Sei-ichiro Kamata, Richard O. Eason and Eiji Kawaguchi
- "Complexity Curves Versus Histograms and Their Application
to Image Segmentation", 1070-1077
Author
Hung Buu Huynh, BLAB, Ifi, UiO
Examples
# Find 4 thersholds values of mona.img
thresMlComCur -nt 4 mona.img
Id
$Id: thresMlComCur.c,v 1.17 1997/01/14 13:07:08 svein Exp $