Edge detection using a simple filter

edge-detection

import cv2
import numpy as np
from scipy import misc
import matplotlib.pyplot as plt

# Getting the image of ascent
i = misc.ascent()

# Ploting the original image
plt.grid(False)
plt.gray()
plt.imshow(i)
plt.show()

# Copying the image in order to apply the kernel filter
i_transformed = np.copy(i)
size_x = i_transformed.shape[0]
size_y = i_transformed.shape[1]

# Defining the filter for edge detection 
filter = [[0, 1, 0], [1, -4, 1], [0, 1, 0]]

# Applying the filter 
for x in range(1,size_x-1):
    for y in range(1,size_y-1):
        convolution = 0.0
        convolution = convolution + (i[x - 1, y-1] * filter[0][0])
        convolution = convolution + (i[x, y-1] * filter[0][1])
        convolution = convolution + (i[x + 1, y-1] * filter[0][2])
        convolution = convolution + (i[x-1, y] * filter[1][0])
        convolution = convolution + (i[x, y] * filter[1][1])
        convolution = convolution + (i[x+1, y] * filter[1][2])
        convolution = convolution + (i[x-1, y+1] * filter[2][0])
        convolution = convolution + (i[x, y+1] * filter[2][1])
        convolution = convolution + (i[x+1, y+1] * filter[2][2])
        if(convolution<0):
            convolution=0
        if(convolution>255):
            convolution=255
        i_transformed[x, y] = convolution
        
# Ploting the transformed image
plt.grid(False)
plt.gray()
plt.imshow(i_transformed)
plt.show()