diff --git a/bob/bio/vein/configurations/maximum_curvature.py b/bob/bio/vein/configurations/maximum_curvature.py
index ba69e197996bc9a0424d72878531c7f0ca412db0..46c86ea792b568c4145d10de7cbe6852e1a96c27 100644
--- a/bob/bio/vein/configurations/maximum_curvature.py
+++ b/bob/bio/vein/configurations/maximum_curvature.py
@@ -20,8 +20,8 @@ or the attribute ``sub_directory`` in a configuration file loaded **after**
this resource.
"""
-from ..preprocessor import Padder, TomesLeeMask, HuangNormalization, NoFilter
-from ..preprocessor import Preprocessor
+from ..preprocessor import NoCropper, Padder, TomesLeeMask, \
+ HuangNormalization, NoFilter, Preprocessor
# Filter sizes for the vertical "high-pass" filter
FILTER_HEIGHT = 4
@@ -32,6 +32,7 @@ PAD_WIDTH = 5
PAD_CONST = 51
preprocessor = Preprocessor(
+ crop=NoCropper(),
mask=TomesLeeMask(filter_height=FILTER_HEIGHT, filter_width=FILTER_WIDTH),
normalize=HuangNormalization(padding_width=PAD_WIDTH,
padding_constant=PAD_CONST),
diff --git a/bob/bio/vein/configurations/repeated_line_tracking.py b/bob/bio/vein/configurations/repeated_line_tracking.py
index 2050174a072c6250d38b0769a7ec429da2ee4fc9..accd87142e541857fce28986a01a43fa9cfeebc2 100644
--- a/bob/bio/vein/configurations/repeated_line_tracking.py
+++ b/bob/bio/vein/configurations/repeated_line_tracking.py
@@ -20,8 +20,8 @@ or the attribute ``sub_directory`` in a configuration file loaded **after**
this resource.
"""
-from ..preprocessor import Padder, TomesLeeMask, HuangNormalization, NoFilter
-from ..preprocessor import Preprocessor
+from ..preprocessor import NoCropper, Padder, TomesLeeMask, \
+ HuangNormalization, NoFilter, Preprocessor
# Filter sizes for the vertical "high-pass" filter
FILTER_HEIGHT = 4
@@ -32,6 +32,7 @@ PAD_WIDTH = 5
PAD_CONST = 51
preprocessor = Preprocessor(
+ crop=NoCropper(),
mask=TomesLeeMask(filter_height=FILTER_HEIGHT, filter_width=FILTER_WIDTH),
normalize=HuangNormalization(padding_width=PAD_WIDTH,
padding_constant=PAD_CONST),
diff --git a/bob/bio/vein/configurations/wide_line_detector.py b/bob/bio/vein/configurations/wide_line_detector.py
index aef74c0e2f8f4cb5b6739ef53ecdd17b5762e185..b82cf420f1a819d8bbd2ffc31f2e314244ae42dc 100644
--- a/bob/bio/vein/configurations/wide_line_detector.py
+++ b/bob/bio/vein/configurations/wide_line_detector.py
@@ -20,8 +20,8 @@ or the attribute ``sub_directory`` in a configuration file loaded **after**
this resource.
"""
-from ..preprocessor import Padder, TomesLeeMask, HuangNormalization, NoFilter
-from ..preprocessor import Preprocessor
+from ..preprocessor import NoCropper, Padder, TomesLeeMask, \
+ HuangNormalization, NoFilter, Preprocessor
# Filter sizes for the vertical "high-pass" filter
FILTER_HEIGHT = 4
@@ -32,6 +32,7 @@ PAD_WIDTH = 5
PAD_CONST = 51
preprocessor = Preprocessor(
+ crop=NoCropper(),
mask=TomesLeeMask(filter_height=FILTER_HEIGHT, filter_width=FILTER_WIDTH),
normalize=HuangNormalization(padding_width=PAD_WIDTH,
padding_constant=PAD_CONST),
diff --git a/bob/bio/vein/preprocessor/__init__.py b/bob/bio/vein/preprocessor/__init__.py
index 7d24970ca55a638d4f29a83364c96f9e873e98bf..d9cb613ded7d164d1aa6978f4557eaf35b027135 100644
--- a/bob/bio/vein/preprocessor/__init__.py
+++ b/bob/bio/vein/preprocessor/__init__.py
@@ -1,4 +1,5 @@
-from .mask import Padder, Masker, NoMask, AnnotatedRoIMask
+from .cropper import Cropper, FixedCropper, NoCropper
+from .mask import Padder, Masker, FixedMask, AnnotatedRoIMask
from .mask import KonoMask, LeeMask, TomesLeeMask
from .normalize import Normalizer, NoNormalization, HuangNormalization
from .filters import Filter, NoFilter, HistogramEqualization
@@ -19,9 +20,12 @@ def __appropriate__(*args):
for obj in args: obj.__module__ = __name__
__appropriate__(
+ Cropper,
+ FixedCropper,
+ NoCropper,
Padder,
Masker,
- NoMask,
+ FixedMask,
AnnotatedRoIMask,
KonoMask,
LeeMask,
diff --git a/bob/bio/vein/preprocessor/cropper.py b/bob/bio/vein/preprocessor/cropper.py
new file mode 100644
index 0000000000000000000000000000000000000000..1dc545471e3f4005da55a6a16d2bde5aed86b45e
--- /dev/null
+++ b/bob/bio/vein/preprocessor/cropper.py
@@ -0,0 +1,107 @@
+#!/usr/bin/env python
+# vim: set fileencoding=utf-8 :
+
+
+'''Base utilities for pre-cropping images'''
+
+import numpy
+
+
+class Cropper(object):
+ """This is the base class for all croppers
+
+ It defines the minimum requirements for all derived cropper classes.
+
+
+ """
+
+ def __init__(self):
+ pass
+
+
+ def __call__(self, image):
+ """Overwrite this method to implement your masking method
+
+
+ Parameters:
+
+ image (numpy.ndarray): A 2D numpy array of type ``uint8`` with the
+ input image
+
+
+ Returns:
+
+ numpy.ndarray: A 2D numpy array of the same type as the input, with
+ cropped rows and columns as per request
+
+ """
+
+ raise NotImplemented('You must implement the __call__ slot')
+
+
+class FixedCropper(object):
+ """Implements cropping using a fixed suppression of border pixels
+
+ The defaults supress no lines from the image and returns an image like the
+ original.
+
+
+ .. note::
+
+ Before choosing values, note you're responsible for knowing what is the
+ orientation of images fed into this cropper.
+
+
+ Parameters:
+
+ top (:py:class:`int`, optional): Number of lines to suppress from the top
+ of the image. The top of the image corresponds to ``y = 0``.
+
+ bottom (:py:class:`int`, optional): Number of lines to suppress from the
+ bottom of the image. The bottom of the image corresponds to ``y =
+ height``.
+
+ left (:py:class:`int`, optional): Number of lines to suppress from the left
+ of the image. The left of the image corresponds to ``x = 0``.
+
+ right (:py:class:`int`, optional): Number of lines to suppress from the
+ right of the image. The right of the image corresponds to ``x = width``.
+
+ """
+
+ def __init__(self, top=0, bottom=0, left=0, right=0):
+ self.top = top
+ self.bottom = bottom
+ self.left = left
+ self.right = right
+
+
+ def __call__(self, image):
+ """Returns a big mask
+
+
+ Parameters:
+
+ image (numpy.ndarray): A 2D numpy array of type ``uint8`` with the
+ input image
+
+
+ Returns:
+
+ numpy.ndarray: A 2D numpy array of type boolean with the caculated
+ mask. ``True`` values correspond to regions where the finger is
+ situated
+
+
+ """
+
+ # this should work even if limits are zeros
+ h, w = image.shape
+ return image[self.top:h-self.bottom, self.left:w-self.right]
+
+
+class NoCropper(FixedCropper):
+ """Convenience: same as FixedCropper()"""
+
+ def __init__(self):
+ super(NoCropper, self).__init__(0, 0, 0, 0)
diff --git a/bob/bio/vein/preprocessor/mask.py b/bob/bio/vein/preprocessor/mask.py
index aa09d17f14edd183a56caccc4ef20131f2810750..b558ae69c22f296e8d9f5a7132b74e732744a47b 100644
--- a/bob/bio/vein/preprocessor/mask.py
+++ b/bob/bio/vein/preprocessor/mask.py
@@ -89,12 +89,41 @@ class Masker(object):
raise NotImplemented('You must implement the __call__ slot')
-class NoMask(object):
- """Implements no masking - i.e. returns a mask the same size as input
+class FixedMask(object):
+ """Implements masking using a fixed suppression of border pixels
+
+ The defaults mask no lines from the image and returns a mask of the same size
+ of the original image where all values are ``True``.
+
+
+ .. note::
+
+ Before choosing values, note you're responsible for knowing what is the
+ orientation of images fed into this masker.
+
+
+ Parameters:
+
+ top (:py:class:`int`, optional): Number of lines to suppress from the top
+ of the image. The top of the image corresponds to ``y = 0``.
+
+ bottom (:py:class:`int`, optional): Number of lines to suppress from the
+ bottom of the image. The bottom of the image corresponds to ``y =
+ height``.
+
+ left (:py:class:`int`, optional): Number of lines to suppress from the left
+ of the image. The left of the image corresponds to ``x = 0``.
+
+ right (:py:class:`int`, optional): Number of lines to suppress from the
+ right of the image. The right of the image corresponds to ``x = width``.
+
"""
- def __init__(self):
- pass
+ def __init__(self, top=0, bottom=0, left=0, right=0):
+ self.top = top
+ self.bottom = bottom
+ self.left = left
+ self.right = right
def __call__(self, image):
@@ -115,7 +144,15 @@ class NoMask(object):
"""
- return numpy.ones(image.shape, dtype='bool')
+ retval = numpy.ones(image.shape, dtype='bool')
+
+ # this should work even if limits are zeros
+ retval[:self.top] = False
+ retval[-self.bottom:] = False
+ retval[:,:self.left] = False
+ retval[:,-self.right:] = False
+
+ return retval
class AnnotatedRoIMask(object):
@@ -428,3 +465,6 @@ class TomesLeeMask(Masker):
else:
w = self.padder.padding_width
return finger_mask[w:-w,w:-w]
+
+
+
diff --git a/bob/bio/vein/preprocessor/preprocessor.py b/bob/bio/vein/preprocessor/preprocessor.py
index f925ef051efcbd5baf9fb83387c81a361b2ec266..549877fbf5860dcc77aa74b420d57d6b083e1119 100644
--- a/bob/bio/vein/preprocessor/preprocessor.py
+++ b/bob/bio/vein/preprocessor/preprocessor.py
@@ -11,7 +11,8 @@ class Preprocessor (BasePreprocessor):
In this implementation, the finger image is (in this order):
- #. The mask is expolated from the image using one of our
+ #. The image is pre-cropped to remove obvious non-finger image parts
+ #. The mask is extrapolated from the image using one of our
:py:class:`Masker`'s concrete implementations
#. The image is normalized with one of our :py:class:`Normalizer`'s
#. The image is filtered with one of our :py:class:`Filter`'s
@@ -19,6 +20,11 @@ class Preprocessor (BasePreprocessor):
Parameters:
+ crop (:py:class:`Cropper`): An object that will perform pre-cropping on
+ the input image before a mask can be estimated. It removes parts of the
+ image which are surely not part of the finger region you'll want to
+ consider for the next steps.
+
mask (:py:class:`Masker`): An object representing a Masker instance which
will extrapolate the mask from the input image.
@@ -34,15 +40,17 @@ class Preprocessor (BasePreprocessor):
"""
- def __init__(self, mask, normalize, filter, **kwargs):
+ def __init__(self, crop, mask, normalize, filter, **kwargs):
BasePreprocessor.__init__(self,
+ crop = crop,
mask = mask,
normalize = normalize,
filter = filter,
**kwargs
)
+ self.crop = crop
self.mask = mask
self.normalize = normalize
self.filter = filter
@@ -66,7 +74,8 @@ class Preprocessor (BasePreprocessor):
"""
- mask = self.mask(data)
+ cropped = self.crop(data)
+ mask = self.mask(cropped)
data, mask = self.normalize(data, mask)
data = self.filter(data, mask)
return data, mask
diff --git a/bob/bio/vein/tests/test.py b/bob/bio/vein/tests/test.py
index b9e1752b80291af52884755b470909957d594138..908d3fb8d01a1f95a1eece3d8fa2f773c5bd00f6 100644
--- a/bob/bio/vein/tests/test.py
+++ b/bob/bio/vein/tests/test.py
@@ -42,10 +42,11 @@ def test_finger_crop():
img = bob.io.base.load(input_filename)
- from bob.bio.vein.preprocessor import Preprocessor, LeeMask, \
+ from bob.bio.vein.preprocessor import Preprocessor, NoCropper, LeeMask, \
HuangNormalization, NoFilter
processor = Preprocessor(
+ NoCropper(),
LeeMask(filter_height=40, filter_width=4),
HuangNormalization(padding_width=0, padding_constant=0),
NoFilter(),
@@ -112,9 +113,10 @@ def test_max_curvature_HE():
input_img = bob.io.base.load(input_img_filename)
# Preprocess the data and apply Histogram Equalization postprocessing (same parameters as in maximum_curvature.py configuration file + postprocessing)
- from bob.bio.vein.preprocessor import Preprocessor, LeeMask, \
+ from bob.bio.vein.preprocessor import Preprocessor, NoCropper, LeeMask, \
HuangNormalization, HistogramEqualization
processor = Preprocessor(
+ NoCropper(),
LeeMask(filter_height=40, filter_width=4),
HuangNormalization(padding_width=0, padding_constant=0),
HistogramEqualization(),
@@ -161,9 +163,10 @@ def test_repeated_line_tracking_HE():
input_img = bob.io.base.load(input_img_filename)
# Preprocess the data and apply Histogram Equalization postprocessing (same parameters as in repeated_line_tracking.py configuration file + postprocessing)
- from bob.bio.vein.preprocessor import Preprocessor, LeeMask, \
+ from bob.bio.vein.preprocessor import Preprocessor, NoCropper, LeeMask, \
HuangNormalization, HistogramEqualization
processor = Preprocessor(
+ NoCropper(),
LeeMask(filter_height=40, filter_width=4),
HuangNormalization(padding_width=0, padding_constant=0),
HistogramEqualization(),
@@ -214,9 +217,10 @@ def test_wide_line_detector_HE():
input_img = bob.io.base.load(input_img_filename)
# Preprocess the data and apply Histogram Equalization postprocessing (same parameters as in wide_line_detector.py configuration file + postprocessing)
- from bob.bio.vein.preprocessor import Preprocessor, LeeMask, \
+ from bob.bio.vein.preprocessor import Preprocessor, NoCropper, LeeMask, \
HuangNormalization, HistogramEqualization
processor = Preprocessor(
+ NoCropper(),
LeeMask(filter_height=40, filter_width=4),
HuangNormalization(padding_width=0, padding_constant=0),
HistogramEqualization(),