bwperim.py

# vim: set ts=4 sts=4 sw=4 expandtab smartindent:
#
# This file was originally part of the octave-forge project
# Ported to python by Luis Pedro Coelho <luis@luispedro.org> (February 2008)
# Copyright (C) 2006       Soren Hauberg
# Copyright (C) 2008-2010  Luis Pedro Coelho (Python port)
# 
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2, or (at your option)
# any later version.
# 
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# General Public License for more details. 
# 
# You should have received a copy of the GNU General Public License
# along with this file.  If not, see <http://www.gnu.org/licenses/>.

import numpy as np

__all__ = ['bwperim']

def bwperim(bw, n=4):
    """
    perim = bwperim(bw, n=4)
    Find the perimeter of objects in binary images.
    A pixel is part of an object perimeter if its value is one and there
    is at least one zero-valued pixel in its neighborhood.
    By default the neighborhood of a pixel is 4 nearest pixels, but
    if `n` is set to 8 the 8 nearest pixels will be considered.
    Parameters
    ----------
      bw : A black-and-white image
      n : Connectivity. Must be 4 or 8 (default: 8)
    Returns
    -------
      perim : A boolean image
    """

    if n not in (4,8):
        raise ValueError('mahotas.bwperim: n must be 4 or 8')
    rows,cols = bw.shape

    # Translate image by one pixel in all directions
    north = np.zeros((rows,cols))
    south = np.zeros((rows,cols))
    west = np.zeros((rows,cols))
    east = np.zeros((rows,cols))

    north[:-1,:] = bw[1:,:]
    south[1:,:]  = bw[:-1,:]
    west[:,:-1]  = bw[:,1:]
    east[:,1:]   = bw[:,:-1]
    idx = (north == bw) & \
          (south == bw) & \
          (west  == bw) & \
          (east  == bw)
    if n == 8:
        north_east = np.zeros((rows, cols))
        north_west = np.zeros((rows, cols))
        south_east = np.zeros((rows, cols))
        south_west = np.zeros((rows, cols))
        north_east[:-1, 1:]   = bw[1:, :-1]
        north_west[:-1, :-1] = bw[1:, 1:]
        south_east[1:, 1:]     = bw[:-1, :-1]
        south_west[1:, :-1]   = bw[:-1, 1:]
        idx &= (north_east == bw) & \
               (south_east == bw) & \
               (south_west == bw) & \
               (north_west == bw)
    return ~idx * bw