[mmcwatershed] [Up] [mmswatershed] Thinning And Thickening

mmskiz
Skeleton of Influence Zone - also know as Generalized Voronoi Diagram

Synopsis

y = mmskiz( f, Bc = None, LINEREG = "LINES", METRIC = None )

Implemented in Python.

Input

f	Image Binary image.
Bc	Structuring Element Connectivity for the distance measurement. Default: `None` (3x3 elementary cross)
LINEREG	String 'LINES' or 'REGIONS'. Default: `"LINES"`
METRIC	String 'EUCLIDEAN' if specified. Default: `None`

Output

y	Image Gray-scale (uint8 or uint16) or binary image.

Description

mmskiz creates the image y by detecting the lines which are equidistant to two or more connected components of f, according to the connectivity defined by Bc. Depending on with the flag LINEREG, y will be a binary image with the skiz lines or a labeled image representing the zone of influence regions. When the connected objects of f are single points, the skiz is the Voronoi diagram.

Examples

Skiz:

>>> f=mmreadgray('blob2.tif')

>>> y=mmskiz(f,mmsebox(),'LINES','EUCLIDEAN')

>>> mmshow(f,y)


f,y

Voronoi diagram:

>>> from Numeric import zeros

>>> f=mmbinary(zeros((100,100)))

>>> f[30,25],f[20,75],f[50,50],f[70,30],f[80,70] = 1,1,1,1,1

>>> y = mmskiz(f,mmsebox(),'LINES','EUCLIDEAN')

>>> mmshow(f,y)


f,y

Limitations

For Euclidean metric, please see mmdist.

Source Code
        def mmskiz(f, Bc=None, LINEREG="LINES", METRIC=None):
    from string import upper
    if Bc is None: Bc = mmsecross()
    LINEREG = upper(LINEREG)
    if METRIC is not None: METRIC = upper(METRIC)
    d = mmdist( mmneg(f), Bc, METRIC)
    return mmcwatershed(d,f,Bc,LINEREG)
    return y
    
      

mmdist	Distance transform.
mmcwatershed	Detection of watershed from markers.

[`mmcwatershed`] [Up] [`mmswatershed`]
Copyright (c) 2003, Roberto A. Lotufo, UNICAMP-University of Campinas; Rubens C. Machado, CenPRA-Renato Archer Research Center.

mmskiz Skeleton of Influence Zone - also know as Generalized Voronoi Diagram