def test_anonimization_sucess(self):
import pydicom
registers = ['PatientName', 'PatientID']
recipe = os.path.join(self.base, 'recipes/confidential')
handler = EPRData(registers, recipe)
# Verifica que efectivamente la imagen original tiene
# los registros PatientName y PatientID
self.image.PatientName
self.image.PatientID
file, data = handler.anonimize(self.image)
# Verifica la eliminación de dichos registros tras la anonimización
ds = pydicom.read_file(file)
with self.assertRaises(AttributeError):
ds.PatientName
with self.assertRaises(AttributeError):
ds.PatientID
# Verificacion de los valores de los registros extraidos
self.assertDictEqual(data, {
'PatientName': 'FRANCISCO^ALVARES^QUESAD',
'PatientID': 'HCMC-18-5456'
}, 'Error extracting confidential data from image')
def test_not_authentic_image(self):
from dhdicom.hidding.mixed import EPRHindingAndAuthentication
import pydicom
filename = os.path.join(self.base, 'images/2.dcm')
image = DicomImage(filename)
ds = pydicom.read_file(filename)
dimesions = ds.Rows, ds.Columns
registers = ['PatientName', 'PatientID']
recipe = os.path.join(self.base, 'recipes/confidential')
epr = EPRData(registers, recipe)
hider = EPRHindingAndAuthentication('nuevaclave')
handler = DHDicomHandler(data_handler=epr, hider_handler=hider)
new_image = handler.process(image)
# Image Tampering
x = dimesions[0] - 1
y = dimesions[1] - 1
pixels = new_image.read()
pixels[0][0] += 1
pixels[x][y] += 1
new_image.write(pixels)
# Despues del procesamiento los pixeles se modificaron
authentic, blocks_tampered = handler.authenticate(new_image)
self.assertFalse(authentic)
# image size: 255x255, block size:32x32, block num: 255
np.testing.assert_array_equal(blocks_tampered, np.array([0, 255]))
def test_load_all_data_success(self):
registers = ['PatientName', 'PatientID']
recipe = os.path.join(self.base, 'recipes/confidential')
handler = EPRData(registers, recipe)
data = handler.read(self.image)
self.assertDictEqual(data, {
'PatientName': 'FRANCISCO^ALVARES^QUESAD',
'PatientID': 'HCMC-18-5456'
}, 'Error extracting confidential data from image')
def test_an_incorrect_register(self):
from dhdicom.exceptions import RegisterNotFound
registers = ['PatientName', 'PatientData']
recipe = os.path.join(self.base, 'recipes/confidential')
handler = EPRData(registers, recipe)
data = handler.read(self.image)
self.assertDictEqual(data, {
'PatientName': 'FRANCISCO^ALVARES^QUESAD',
'PatientData': None
}, 'Error extracting confidential data from image')
def test_authentic_image(self):
from dhdicom.hidding.mixed import EPRHindingAndAuthentication
filename = os.path.join(self.base, 'images/2.dcm')
image = DicomImage(filename)
registers = ['PatientName', 'PatientID']
recipe = os.path.join(self.base, 'recipes/confidential')
epr = EPRData(registers, recipe)
hider = EPRHindingAndAuthentication('nuevaclave')
handler = DHDicomHandler(data_handler=epr, hider_handler=hider)
new_image = handler.process(image)
authentic, *l = handler.authenticate(new_image)
self.assertTrue(authentic)
# No hay bloques modificados
self.assertFalse(l)
def test_get_message(self):
from dhdicom.hidding.mixed import EPRHindingAndAuthentication
import pydicom
filename = os.path.join(self.base, 'images/2.dcm')
image = DicomImage(filename)
ds = pydicom.read_file(filename)
registers = ['PatientName', 'PatientID']
patient_name = ds.PatientName
patient_id = ds.PatientID
recipe = os.path.join(self.base, 'recipes/confidential')
epr = EPRData(registers, recipe)
data = epr.read(image)
hider = EPRHindingAndAuthentication('nuevaclave')
handler = DHDicomHandler(data_handler=epr, hider_handler=hider)
new_image = handler.process(image)
self.assertEqual(data, handler.get_epr(new_image))
def __init__(self, parent=None):
# inicializar el padre
super(VentanaPrincipal, self).__init__(parent)
# configurar la interfaz
self.setupUi(self)
self.original_image = None
self.watermarked_image = None
self.hiddenEPRTable.setHorizontalHeaderLabels(["Register", "Value"])
self.eprTable.setHorizontalHeaderLabels(["Register", "Value"])
self.actionAbrir.triggered.connect(self.Cargar_imagen)
self.actionSalvar.triggered.connect(self.Salvar_imagen)
self.actionCropping.triggered.connect(self.crop_image)
self.btn_procesar.clicked.connect(self.Procesar_imagen)
self.btnExtractAuthenticate.clicked.connect(self.analizar)
self.init_canvas()
# Registros EPR
base = os.path.dirname(os.path.dirname(__file__))
self.epr = EPRData(settings.EPR_TO_HIDE, settings.RECIPE_FILE)
self.hider = EPRHindingAndAuthentication('nuevaclave')
def main():
# Keys
key = "Aslorent7N;fpr-y5"
base = os.path.dirname(__file__)
# Directory
dir = "tests/dicom"
if not os.path.exists(dir): os.makedirs(dir)
try:
root = Tk()
filename = filedialog.askopenfilenames(
parent=root, initialdir=dir, title='Please select a directory')
# Load cover image (array)
cover = DicomImage(filename[0])
except Exception:
raise ValueError("The image files were not loaded")
root.destroy()
# Creating matrix
M_Metrics = []
# Creating directory
dir_dat_file = os.path.join("dhdicom", "static", "Results")
if not os.path.exists(dir_dat_file): os.makedirs(dir_dat_file)
dir_dat_file = os.path.join(dir_dat_file, filename[0].split("/")[-2])
dir_dat_file = "%s_Results.dat" % dir_dat_file
# Instance
metr = Metrics()
# Building stego images. Generating results
for i in range(len(filename)):
row = []
# Generating keys
key = utils.sha256_to_key_bin(key)
image = DicomImage(filename[i])
registers = ['PatientName', 'PatientID']
recipe = os.path.join(base, 'recipes/confidential')
epr = EPRData(registers, recipe)
hider = EPRHindingAndAuthentication(key)
handler = DHDicomHandler(data_handler=epr, hider_handler=hider)
new_image = handler.process(image)
cover_array = image.read()
watermarked_array = new_image.read()
# Experimental analysis
row.append(metr.psnr(cover_array, watermarked_array))
row.append(metr.uiqi(cover_array, watermarked_array))
row.append(metr.image_fid(cover_array, watermarked_array))
print(" ")
print("Experimental analysis")
print(" ")
print("PSNR: ", row[0])
print(" ")
print("UIQI: ", row[1])
print(" ")
print("IF: ", row[2])
print(" ")
# Creating cols
M_Metrics.append(row)
# Saving results
np.savetxt(dir_dat_file, M_Metrics, fmt="%.9e")
# Saving results
np.savetxt(dir_dat_file, M_Metrics, fmt="%.9e")