To write and execute image processing programs using point processing method

 a. Obtain Negative image Program: 

 import cv2 

 img = cv2.imread("C:/Users/welcome/Desktop/sem6/DIP/Nature.png") 

 cv2.imshow("Original_image", img) 

 img1=255-img 

 cv2.imshow("Negative_image", img1) 

 cv2.waitKey(0) 

 cv2.destroyAllWindows()

b.Obtain Flip image  

Program: 

import cv2 

img = cv2.imread("C:/Users/welcome/Desktop/sem6/DIP/Nature.png") 

horizontal_flip = cv2.flip(img, 1)  

vertical_flip = cv2.flip(img, 0)  

both_flip = cv2.flip(img, -1)  

cv2.imshow("Original_image", img) 

cv2.imshow("horizontal_flip_image", horizontal_flip) 

cv2.imshow("vertical_flip_image", vertical_flip) 

cv2.imshow("both_flip_image", both_flip) 

cv2.waitKey(0)  

cv2.destroyAllWindows()

c. Thresholding  

Program: 

import cv2 

img = cv2.imread("C:/Users/welcome/Desktop/sem6/DIP/Nature.png", 

cv2.IMREAD_GRAYSCALE) 

adaptive_thresh = cv2.adaptiveThreshold( 

    img, 255,                       

    cv2.ADAPTIVE_THRESH_GAUSSIAN_C,   

    cv2.THRESH_BINARY,        

    11, 2                          

) 

cv2.imshow("Original_image", img) 

cv2.imshow("Adaptive Thresholding", adaptive_thresh) 

cv2.waitKey(0) 

cv2.destroyAllWindows()

d.Contrast stretching  

Program: 

import numpy as np 

import cv2 

img = cv2.imread("C:/Users/welcome/Desktop/sem6/DIP/Nature.png") 

min_val = np.min(img) 

max_val = np.max(img) 

stretched = ((img - min_val) * (255.0 / (max_val - 

min_val))).astype(np.uint8) 

 

cv2.imshow("Original_image", img) 

cv2.imshow("contrast_stretched", stretched) 

cv2.waitKey(0) 

cv2.destroyAllWindows()

Write given 2-D data in image file

 import numpy as np 

 import cv2 

 data=np.array([[255,0,255,0],[0,255,0,255],[255,0,255,0],[0,255,0,255]], dtype=np.uint8)

 cv2.imwrite('output_image.png',data) 

 cv2.imshow('image',data) 

 cv2.waitKey(0) 

 cv2.destroyAllWindows()

Create color image using R, G and B three separate planes. Program:

 import cv2 img = cv2.imread("C:/Users/welcome/Desktop/sem6/DIP/Lenna.png") cv2.imshow("Original_image", img) b,g,r=cv2.split(img) merge_bgr=cv2.merge((b,g,r)) cv2.imshow("Merge_image", merge_bgr) cv2.waitKey(0) cv2.destroyAllWindows()

Write given 2D image file program

 

Create color image using R, G and B three separate planes

 import cv2

import numpy as np

height, width = 300, 300

R = np.full((height, width), 255, dtype=np.uint8) # Red plane (fully red)

G = np.zeros((height, width), dtype=np.uint8) # Green plane (zero)

B = np.full((height, width), 100, dtype=np.uint8) # Blue plane (some blue)

color_image = cv2.merge([B, G, R])

cv2.imshow("Color Image from R, G, B Planes", color_image)

cv2.waitKey(0)

cv2.destroyAllWindows()

Draw image profile

 import cv2

import numpy as np

import matplotlib.pyplot as plt

image = cv2.imread('your_image.jpg', cv2.IMREAD_GRAYSCALE)

row = image.shape[0] // 2 # Middle row

profile = image[row, :] # Intensity values along that row

image_with_line = cv2.cvtColor(image, cv2.COLOR_GRAY2BGR)

cv2.line(image_with_line, (0, row), (image.shape[1], row), (0, 0, 255), 1)

cv2.imshow("Image with Profile Line", image_with_line)

plt.figure(figsize=(10, 4))

plt.title(f'Intensity Profile of Row {row}')

plt.plot(profile, color='black')

plt.xlabel('Column Index')

plt.ylabel('Intensity')

plt.grid(True)

plt.tight_layout()

plt.show()

cv2.waitKey(0)

cv2.destroyAllWindows()

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