Merge branch 'master' of github.com:taddeus/licenseplates

src/LBP.py

+#!/usr/bin/python
+import Image
+from numpy import array, zeros, byte
+from matplotlib.pyplot import imshow, subplot, show, axis
+
 # Divide the examined window to cells (e.g. 16x16 pixels for each cell).
 
-# For each pixel in a cell, compare the pixel to each of its 8 neighbors 
-# (on its left-top, left-middle, left-bottom, right-top, etc.). Follow the 
+# For each pixel in a cell, compare the pixel to each of its 8 neighbors
+# (on its left-top, left-middle, left-bottom, right-top, etc.). Follow the
 # pixels along a circle, i.e. clockwise or counter-clockwise.
-    
-# Where the center pixel's value is greater than the neighbor, write "1". 
-# Otherwise, write "0". This gives an 8-digit binary number (which is usually 
+
+# Where the center pixel's value is greater than the neighbor, write "1".
+# Otherwise, write "0". This gives an 8-digit binary number (which is usually
 # converted to decimal for convenience).
 
-# Compute the histogram, over the cell, of the frequency of each "number" 
-# occurring (i.e., each combination of which pixels are smaller and which are 
+# Compute the histogram, over the cell, of the frequency of each "number"
+# occurring (i.e., each combination of which pixels are smaller and which are
 # greater than the center).
-    
-# Optionally normalize the histogram. Concatenate normalized histograms of all 
+
+# Optionally normalize the histogram. Concatenate normalized histograms of all
 # cells. This gives the feature vector for the window.
+
+CELL_SIZE = 16
+
+def domain_iterator(shape):
+    """Iterate over the pixels of an image."""
+    for y in xrange(shape[0]):
+        for x in xrange(shape[1]):
+            yield y, x
+
+image = array(Image.open('../images/test.png').convert('L'))
+
+def in_image(y, x, F):
+    """Check if given pixel coordinates are within the bounds of image F."""
+    return 0 <= y < F.shape[0] and 0 <= x < F.shape[1]
+
+def features(image):
+    """Compare each pixel to each of its eight neigheach pixel to each of its
+    eight neighbours."""
+    features = zeros(image.shape, dtype=byte)
+
+    def cmp_pixels(y, x, p):
+        return in_image(y, x, image) and image[y, x] > p
+
+    for y, x in domain_iterator(features.shape):
+        p = image[y, x]
+
+        # Walk around the pixel in counter-clokwise order, shifting 1 but less
+        # at each neighbour starting at 7 in the top-left corner. This gives a
+        # 8-bitmap
+        features[y, x] = byte(cmp_pixels(y - 1, x - 1, p)) << 7 \
+                         | byte(cmp_pixels(y - 1, x, p)) << 6 \
+                         | byte(cmp_pixels(y - 1, x + 1, p)) << 5 \
+                         | byte(cmp_pixels(y, x + 1, p)) << 4 \
+                         | byte(cmp_pixels(y + 1, x + 1, p)) << 3 \
+                         | byte(cmp_pixels(y + 1, x, p)) << 2 \
+                         | byte(cmp_pixels(y + 1, x - 1, p)) << 1 \
+                         | byte(cmp_pixels(y, x - 1, p))
+
+    return features
+
+def feature_vectors(image):
+    """Create cell histograms of an image"""
+    F = features(image)
+
+V = feature_vectors(image)
+subplot(121)
+imshow(image, cmap='gray')
+subplot(122)
+imshow(V, cmap='gray')
+axis('off')
+show()