def feature_extraction_single_rolled(self, img_file):
block_size = 16
if not os.path.exists(img_file):
return None
img = io.imread(img_file)
h, w = img.shape
mask = get_maps.get_quality_map_intensity(img)
#if np.max(mask) == 0:
# print img_file
#return None
start = timeit.default_timer()
mnt = self.minu_model.run_whole_image(img, minu_thr=0.2)
stop = timeit.default_timer()
minu_time = stop - start
# show.show_minutiae(img, mnt, mask=mask, block=True, fname=None)
# show.show_minutiae(img,mnt)
# start = timeit.default_timer()
des = descriptor.minutiae_descriptor_extraction(
img,
mnt,
self.patch_types,
self.des_models,
self.patchIndexV,
batch_size=256,
patch_size=self.patch_size)
# stop = timeit.default_timer()
# des_time = stop - start
print minu_time #, des_time
#texture_img = preprocessing.FastCartoonTexture(img, sigma=2.5, show=False)
dir_map, _ = get_maps.get_maps_STFT(img,
patch_size=64,
block_size=block_size,
preprocess=True)
#stop = timeit.default_timer()
blkH = h // block_size
blkW = w // block_size
# dir_map = np.zeros((blkH,blkW))
# print stop - start
#blkH, blkW = dir_map.shape
minu_template = template.MinuTemplate(h=h,
w=w,
blkH=blkH,
blkW=blkW,
minutiae=mnt,
des=des,
oimg=dir_map,
mask=mask)
rolled_template = template.Template()
rolled_template.add_minu_template(minu_template)
return rolled_template
def feature_extraction_longitudinal(self, img_file):
block_size = 16
img = io.imread(img_file)
#print img.shape
img = preprocessing.adjust_image_size(img, block_size)
h, w = img.shape
texture_img = preprocessing.FastCartoonTexture(img,
sigma=2.5,
show=False)
contrast_img_guassian = preprocessing.local_constrast_enhancement_gaussian(
img)
mask = get_maps.get_quality_map_intensity(img)
#show.show_mask(mask, img, fname=None, block=True)
quality_map, dir_map, fre_map = get_maps.get_quality_map_dict(
texture_img,
self.dict_all,
self.dict_ori,
self.dict_spacing,
block_size=16,
process=False)
enh_constrast_img = filtering.gabor_filtering_pixel(
contrast_img_guassian,
dir_map + math.pi / 2,
fre_map,
mask=np.ones((h, w), np.int),
block_size=16,
angle_inc=3)
mnt = self.minu_model.run(img, minu_thr=0.2)
#show.show_minutiae(img,mnt)
des = descriptor.minutiae_descriptor_extraction(img,
mnt,
self.patch_types,
self.des_models,
self.patchIndexV,
batch_size=128)
blkH, blkW = dir_map.shape
minu_template = template.MinuTemplate(h=h,
w=w,
blkH=blkH,
blkW=blkW,
minutiae=mnt,
des=des,
oimg=dir_map,
mask=mask)
rolled_template = template.Template()
rolled_template.add_minu_template(minu_template)
return rolled_template, texture_img, enh_constrast_img
def feature_extraction_single_rolled(self, img_file):
block_size = 16
img = io.imread(img_file)
h, w = img.shape
mask = get_maps.get_quality_map_intensity(img)
mnt = self.minu_model.run(img, minu_thr=0.2)
# show.show_minutiae(img,mnt)
des = descriptor.minutiae_descriptor_extraction(img,
mnt,
self.patch_types,
self.des_models,
self.patchIndexV,
batch_size=128)
#texture_img = preprocessing.FastCartoonTexture(img, sigma=2.5, show=False)
start = timeit.default_timer()
dir_map, _ = get_maps.get_maps_STFT(img,
patch_size=64,
block_size=block_size,
preprocess=True)
stop = timeit.default_timer()
print stop - start
blkH, blkW = dir_map.shape
minu_template = template.MinuTemplate(h=h,
w=w,
blkH=blkH,
blkW=blkW,
minutiae=mnt,
des=des,
oimg=dir_map,
mask=mask)
rolled_template = template.Template()
rolled_template.add_minu_template(minu_template)
return rolled_template
def feature_extraction_single_rolled(self,
img_file,
output_path=None,
ppi=500):
block_size = 16
if not os.path.exists(img_file):
return None
img = io.imread(img_file, s_grey=True)
if ppi != 500:
img = cv2.resize(img, (0, 0), fx=500.0 / ppi, fy=500.0 / ppi)
img = preprocessing.adjust_image_size(img, block_size)
if len(img.shape) > 2:
img = rgb2gray(img)
h, w = img.shape
start = timeit.default_timer()
mask = get_maps.get_quality_map_intensity(img)
stop = timeit.default_timer()
print('time for cropping : %f' % (stop - start))
start = timeit.default_timer()
contrast_img = preprocessing.local_constrast_enhancement(img)
mnt = self.minu_model.run_whole_image(contrast_img, minu_thr=0.1)
stop = timeit.default_timer()
minu_time = stop - start
print('time for minutiae : %f' % (stop - start))
name = os.path.basename(img_file)
show.show_minutiae(img, mnt, block=True)
return None
start = timeit.default_timer()
des = descriptor.minutiae_descriptor_extraction(
img,
mnt,
self.patch_types,
self.des_models,
self.patchIndexV,
batch_size=256,
patch_size=self.patch_size)
stop = timeit.default_timer()
print('time for descriptor : %f' % (stop - start))
dir_map, _ = get_maps.get_maps_STFT(img,
patch_size=64,
block_size=block_size,
preprocess=True)
blkH = h // block_size
blkW = w // block_size
minu_template = template.MinuTemplate(h=h,
w=w,
blkH=blkH,
blkW=blkW,
minutiae=mnt,
des=des,
oimg=dir_map,
mask=mask)
rolled_template = template.Template()
rolled_template.add_minu_template(minu_template)
start = timeit.default_timer()
# texture templates
stride = 16
x = np.arange(24, w - 24, stride)
y = np.arange(24, h - 24, stride)
virtual_minutiae = []
distFromBg = scipy.ndimage.morphology.distance_transform_edt(mask)
for y_i in y:
for x_i in x:
if (distFromBg[y_i][x_i] <= 24):
continue
ofY = int(y_i / 16)
ofX = int(x_i / 16)
ori = -dir_map[ofY][ofX]
virtual_minutiae.append([x_i, y_i, ori])
virtual_minutiae = np.asarray(virtual_minutiae)
if len(virtual_minutiae) > 1000:
virtual_minutiae = virtual_minutiae[:1000]
print len(virtual_minutiae)
if len(virtual_minutiae) > 3:
virtual_des = descriptor.minutiae_descriptor_extraction(
contrast_img,
virtual_minutiae,
self.patch_types,
self.des_models,
self.patchIndexV,
batch_size=128)
texture_template = template.TextureTemplate(
h=h,
w=w,
minutiae=virtual_minutiae,
des=virtual_des,
mask=mask)
rolled_template.add_texture_template(texture_template)
stop = timeit.default_timer()
print('time for texture : %f' % (stop - start))
return rolled_template
def feature_extraction_single_rolled_enhancement(self, img_file):
block_size = 16
img = io.imread(img_file)
# print img.shape
img = preprocessing.adjust_image_size(img, block_size)
h, w = img.shape
#texture_img = preprocessing.FastCartoonTexture(img, sigma=2.5, show=False)
contrast_img_guassian = preprocessing.local_constrast_enhancement_gaussian(
img)
mask = get_maps.get_quality_map_intensity(img)
#show.show_mask(mask, img, fname=None, block=True)
start = timeit.default_timer()
quality_map, dir_map, fre_map = get_maps.get_quality_map_dict(
contrast_img_guassian,
self.dict_all,
self.dict_ori,
self.dict_spacing,
block_size=16,
process=False)
stop = timeit.default_timer()
OF_time = stop - start
print 'of estimate time: %f' % (OF_time)
start = timeit.default_timer()
enh_constrast_img = filtering.gabor_filtering_pixel2(
contrast_img_guassian,
dir_map + math.pi / 2,
fre_map,
mask=mask,
gabor_filters=self.gabor_filters)
stop = timeit.default_timer()
filtering_time = stop - start
print 'filtering time: %f' % (filtering_time)
mnt = self.minu_model.run_whole_image(img, minu_thr=0.2)
# show.show_minutiae(img,mnt)
des = descriptor.minutiae_descriptor_extraction(img,
mnt,
self.patch_types,
self.des_models,
self.patchIndexV,
batch_size=128)
blkH, blkW = dir_map.shape
minu_template = template.MinuTemplate(h=h,
w=w,
blkH=blkH,
blkW=blkW,
minutiae=mnt,
des=des,
oimg=dir_map,
mask=mask)
rolled_template = template.Template()
rolled_template.add_minu_template(minu_template)
# texture templates
stride = 32
x = np.arange(24, w - 24, stride)
y = np.arange(24, h - 24, stride)
virtual_minutiae = []
distFromBg = scipy.ndimage.morphology.distance_transform_edt(mask)
for y_i in y:
for x_i in x:
if (distFromBg[y_i][x_i] <= 16):
continue
ofY = int(y_i / 16)
ofX = int(x_i / 16)
ori = -dir_map[ofY][ofX]
# print("ori = " + str(ori))
virtual_minutiae.append([x_i, y_i,
ori]) #, distFromBg[y_i,x_i]
virtual_minutiae = np.asarray(virtual_minutiae)
if len(virtual_minutiae) > 3:
virtual_des = descriptor.minutiae_descriptor_extraction(
img,
virtual_minutiae,
self.patch_types,
self.des_models,
self.patchIndexV,
batch_size=128)
#show.show_minutiae(img,virtual_minutiae)
texture_template = template.TextureTemplate(
h=h,
w=w,
minutiae=virtual_minutiae,
des=virtual_des,
mask=mask)
rolled_template.add_texture_template(texture_template)
return rolled_template, enh_constrast_img