def calibration(filename):
if not utils.which("convert"):
print("Error: 'convert' tool not found, please install it.\n")
sys.exit(0)
tmpdir = tempfile.mkdtemp()
predfile = os.path.join(tempfile.mkdtemp(), 'pred.jpg')
os.system("convert -chop 2x2 " + filename + " " + predfile)
im_jpeg = JPEG(filename)
impred_jpeg = JPEG(predfile)
found = False
for i in range(im_jpeg.components()):
dct = np.abs(im_jpeg.coeffs(i).flatten())
dctpred = np.abs(impred_jpeg.coeffs(i).flatten())
Hs0 = sum(dct == 0)
Hs1 = sum(dct == 1)
Hp0 = sum(dctpred == 0)
Hp1 = sum(dctpred == 1)
Hp2 = sum(dctpred == 2)
beta = (Hp1 * (Hs0 - Hp0) + (Hs1 - Hp1) *
(Hp2 - Hp1)) / (Hp1**2 + (Hp2 - Hp1)**2)
# XXX: Incomplete implementation. Check http://www.ws.binghamton.edu/fridrich/Research/mms100.pdf
if beta > 0.05:
print("Hiden data found in channel " + str(i) + ":", beta)
found = True
if not found:
print("No hidden data found")
shutil.rmtree(tmpdir)
def print_dct_diffs(cover, stego):
def print_list(l, ln):
for i in range(0, len(l), ln):
print(l[i:i + ln])
C_jpeg = JPEG(cover)
S_jpeg = JPEG(stego)
for i in range(C_jpeg.components()):
C = C_jpeg.coeffs(i)
S = S_jpeg.coeffs(i)
D = S - C
print("\nChannel " + str(i) + ":")
pairs = list(zip(C.ravel(), S.ravel(), D.ravel()))
pairs_diff = [p for p in pairs if p[2] != 0]
print_list(pairs_diff, 5)
def print_dct_diffs(cover, stego):
def print_list(l, ln):
mooc = 0
for i in range(0, len(l), ln):
#print(l[i:i+ln])
v = l[i:i + ln][0][2]
if np.abs(v) > 1:
mooc += 1
print("mooc:", mooc)
C_jpeg = JPEG(cover)
S_jpeg = JPEG(stego)
for i in range(C_jpeg.components()):
C = C_jpeg.coeffs(i)
S = S_jpeg.coeffs(i)
D = S - C
print("\nChannel " + str(i) + ":")
pairs = list(zip(C.ravel(), S.ravel(), D.ravel()))
pairs_diff = [p for p in pairs if p[2] != 0]
#print_list(pairs_diff, 5)
print_list(pairs_diff, 1)
def calibration_f5_octave_jpeg(filename):
""" It uses JPEG from octave """
tmpdir = tempfile.mkdtemp()
predfile = os.path.join(tmpdir, 'img.jpg')
os.system("convert -chop 4x4 "+filename+" "+predfile)
im_jpeg = JPEG(filename)
impred_jpeg = JPEG(predfile)
for i in range(im_jpeg.components()):
dct_b = im_jpeg.coeffs(i)
dct_0 = impred_jpeg.coeffs(i)
b01 = beta_kl(dct_0, dct_b, 0, 1)
b10 = beta_kl(dct_0, dct_b, 1, 0)
b11 = beta_kl(dct_0, dct_b, 1, 1)
beta = (b01+b10+b11)/3
if beta > 0.05:
print("Hidden data found in channel "+str(i)+":", beta)
else:
print("No hidden data found in channel "+str(i))
shutil.rmtree(tmpdir)
def calibration(filename):
tmpdir = tempfile.mkdtemp()
predfile = os.path.join(tmpdir, 'img.jpg')
os.system("convert -chop 4x4 " + filename + " " + predfile)
im_jpeg = JPEG(filename)
impred_jpeg = JPEG(predfile)
found = False
for i in range(im_jpeg.components()):
dct_b = im_jpeg.coeffs(i)
dct_0 = impred_jpeg.coeffs(i)
b01 = beta_kl(dct_0, dct_b, 0, 1)
b10 = beta_kl(dct_0, dct_b, 1, 0)
b11 = beta_kl(dct_0, dct_b, 1, 1)
beta = (b01 + b10 + b11) / 3
if beta > 0.02:
print("Hidden data found in channel " + str(i) + ":", beta)
found = True
if not found:
print("No hidden data found", beta)
shutil.rmtree(tmpdir)