# -*- python -*-
#
# Copyright INRIA - CIRAD - INRA
#
# Distributed under the Cecill-C License.
# See accompanying file LICENSE.txt or copy at
# http://www.cecill.info/licences/Licence_CeCILL-C_V1-en.html
#
# ==============================================================================
"""
Post-processing algorithms to improve binarization of an image
"""
# ==============================================================================
from __future__ import division, print_function
import numpy
import skimage
# ==============================================================================
[docs]
def dilate_erode(binary_image, kernel_shape=(2, 2), iterations=1, mask=None):
"""
Applied a morphology (dilate & erode) on binary_image on a ROI.
Parameters
----------
binary_image : numpy.ndarray
2-D array
kernel_shape: (N, M) of integers, optional
kernel shape of (dilate & erode) applied to binary_image
iterations: int, optional
number of successive iteration of (dilate & erode)
mask : numpy.ndarray, optional
Array of same shape as `image`. Only points at which mask == True
will be processed.
Returns
-------
out : numpy.ndarray
Binary Image
"""
# ==========================================================================
# Check Parameters
if not isinstance(binary_image, numpy.ndarray):
raise TypeError("binary_image must be a numpy.ndarray")
if binary_image.ndim != 2:
raise ValueError("image must be 2D array")
if mask is not None:
if not isinstance(mask, numpy.ndarray):
raise TypeError("mask must be a numpy.ndarray")
if mask.ndim != 2:
raise ValueError("mask must be 2D array")
# ==========================================================================
if mask is not None:
out = numpy.bitwise_and(binary_image, mask)
else:
out = binary_image.copy()
element = numpy.pad(numpy.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]]), kernel_shape)
for _ in range(iterations):
out = skimage.morphology.dilation(out, element)
for _ in range(iterations):
out = skimage.morphology.erosion(out, element)
if mask is not None:
res = numpy.subtract(binary_image, mask)
out = numpy.add(res, out)
return out
[docs]
def erode_dilate(binary_image, kernel_shape=(2, 2), iterations=1, mask=None):
"""
Applied a morphology (erode & dilate) on binary_image on mask ROI.
Parameters
----------
binary_image : numpy.ndarray
2-D array
kernel_shape: (N, M) of integers, optional
kernel shape of (erode & dilate) applied to binary_image
iterations: int, optional
number of successive iteration of (erode & dilate)
mask : numpy.ndarray, optional
Array of same shape as `image`. Only points at which mask == True
will be processed.
Returns
-------
out : numpy.ndarray
Binary Image
"""
# ==========================================================================
# Check Parameters
if not isinstance(binary_image, numpy.ndarray):
raise TypeError("binary_image must be a numpy.ndarray")
if binary_image.ndim != 2:
raise ValueError("binary_image must be 2D array")
if mask is not None:
if not isinstance(mask, numpy.ndarray):
raise TypeError("mask must be a numpy.ndarray")
if mask.ndim != 2:
raise ValueError("mask must be 2D array")
# ==========================================================================
if mask is not None:
out = numpy.bitwise_and(binary_image, mask)
else:
out = binary_image.copy()
element = numpy.pad(numpy.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]]), kernel_shape)
for _ in range(iterations):
out = skimage.morphology.erosion(out, element)
for _ in range(iterations):
out = skimage.morphology.dilation(out, element)
if mask is not None:
res = numpy.subtract(binary_image, mask)
out = numpy.add(res, out)
return out
[docs]
def close(binary_image, kernel_shape=(6, 6), mask=None):
"""
Applied a morphology close on binary_image on mask ROI.
Parameters
----------
binary_image : numpy.ndarray
2-D array
kernel_shape: (N, M) of integers
kernel shape of morphology close applied to binary_image
mask : numpy.ndarray, optional
Array of same shape as `image`. Only points at which mask == True
will be processed.
Returns
-------
out : numpy.ndarray
Binary Image
"""
# ==========================================================================
# Check Parameters
if not isinstance(binary_image, numpy.ndarray):
raise TypeError("image must be a numpy.ndarray")
if binary_image.ndim != 2:
raise ValueError("image must be 2D array")
if mask is not None:
if not isinstance(mask, numpy.ndarray):
raise TypeError("mask must be a numpy.ndarray")
if mask.ndim != 2:
raise ValueError("mask must be 2D array")
# ==========================================================================
if mask is not None:
out = numpy.bitwise_and(binary_image, mask)
else:
out = binary_image.copy()
kernel = numpy.ones(kernel_shape, numpy.uint8)
out = skimage.morphology.closing(out, kernel)
if mask is not None:
out = numpy.add(binary_image, out)
return out
