Python Image Processing Cookbook

LoG/zero-crossing

Perform the following steps to implement edge detection with LoG and zero-crossing:

1. First, let's define the any_neighbor_zero() function that takes a pixel in an image as input and returns True if any of the pixel's (8-connected) neighbors are zero:

def any_neighbor_zero(img, i, j): for k in range(-1,2):   for l in range(-1,2):     if k == 0 and l == 0: continue # skip the input pixel     if img[i+k, j+k] == 0:        return True return False

2. Next, let's define the zero_crossing() function:

def zero_crossing(img): img[img > 0] = 1 img[img < 0] = 0 out_img = np.zeros(img.shape) for i in range(1,img.shape[0]-1):  for j in range(1,img.shape[1]-1):    if img[i,j] > 0 and any_neighbor_zero(img, i, j):       out_img[i,j] = 255 return out_img

3. Finally, ...