refactor image hashing function

khandy/image/image_hash.py

@@ -3,49 +3,67 @@ import khandy
 import numpy as np
 
 
+def _convert_bool_matrix_to_int(bool_mat):
+    hash_val = int(0)
+    for item in bool_mat.flatten():
+        hash_val |= int(item)
+        hash_val <<= 1
+    hash_val >>= 1
+    return hash_val
+    
+    
 def calc_image_ahash(image):
+    """Average Hashing
+
+    References:
+        http://www.hackerfactor.com/blog/index.php?/archives/432-Looks-Like-It.html
+    """
     assert khandy.is_numpy_image(image)
     if image.ndim == 3:
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
     resized = cv2.resize(image, (8, 8))
-
-    meanval = cv2.mean(resized)[0]
-    hashval = int(0)
-    for i in range(8):
-        for j in range(8):
-            mask = int(resized[i,j] - meanval >= 1e-5)
-            hashval |= mask << (i * 8 + j)
-    return hashval
-
     
-def calc_image_phash(image):
+    mean_val = np.mean(resized)
+    hash_mat = resized >= mean_val
+    hash_val = _convert_bool_matrix_to_int(hash_mat)
+    return hash_val
+    
+    
+def calc_image_dhash(image):
+    """Difference Hashing
+
+    References:
+        http://www.hackerfactor.com/blog/index.php?/archives/432-Looks-Like-It.html
+    """
     assert khandy.is_numpy_image(image)
     if image.ndim == 3:
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    resized = cv2.resize(image, (32, 32))
-
-    dft = cv2.dft(resized.astype(np.float32))
-    meanval = cv2.mean(dft[:8,:8])[0]
-    hashval = int(0)
-    for i in range(8):
-        for j in range(8):
-            mask = int(dft[i,j] - meanval >= 1e-5)
-            hashval |= mask << (i * 8 + j)
-    return hashval
-
+    resized = cv2.resize(image, (9, 8))
     
-def calc_image_dhash(image):
+    hash_mat = resized[:,:-1] >= resized[:,1:]
+    hash_val = _convert_bool_matrix_to_int(hash_mat)
+    return hash_val
+    
+    
+def calc_image_phash(image):
+    """Perceptual Hashing
+    
+    References:
+        http://www.hackerfactor.com/blog/index.php?/archives/432-Looks-Like-It.html
+    """
     assert khandy.is_numpy_image(image)
     if image.ndim == 3:
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-    resized = cv2.resize(image, (9, 8))
+    resized = cv2.resize(image, (32, 32))
 
-    hashval = int(0)
-    for i in range(8):
-        for j in range(8):
-            mask = int(resized[i,j] > resized[i,j+1])
-            hashval |= mask << (i * 8 + j)
-    return hashval
-    
+    dct_coeff = cv2.dct(resized.astype(np.float32))
+    reduced_dct_coeff = dct_coeff[:8, :8]
     
+    # median of coefficients excluding the DC term (0th term)
+    # mean_val = np.mean(reduced_dct_coeff.flatten()[1:])
+    median_val = np.median(reduced_dct_coeff.flatten()[1:])
+
+    hash_mat = reduced_dct_coeff >= median_val
+    hash_val = _convert_bool_matrix_to_int(hash_mat)
+    return hash_val
     

khandy/version.py

@@ -1,3 +1,3 @@
-__version__ = '0.1.6'
+__version__ = '0.1.7'
 
 __all__ = ['__version__']

setup.py

@@ -5,7 +5,7 @@ install_requires = ['numpy>=1.11.1', 'opencv-python', 'pillow']
 
 setup(
     name='khandy',
-    version='0.1.6',
+    version='0.1.7',
     description='Handy Utilities for Computer Vision',
     long_description='Handy Utilities for Computer Vision',
     keywords='computer vision',