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09.Image binarization

Image binarization

Image binarization1. Implementation principle2. Implementation effect3. Implementation code

1. Implementation principle

Use cv2.threshold() function to binarize the image.

2. Implementation effect


cd ~/opencv


xxxxxxxxxx
python3 09.image_binarize.py

Note: Select the image and press q to exit the program!

3. Implementation code


x
import cv2
def binarize_image(input_path, output_path, threshold):
    image = cv2.imread(input_path, cv2.IMREAD_GRAYSCALE)
    if image is None:
        print("Error: Unable to open image file.")
        return
    _, binary_image = cv2.threshold(image, threshold, 255, cv2.THRESH_BINARY)
    if cv2.imwrite(output_path, binary_image):
        print(f"Image saved to {output_path}")
        cv2.imshow('Image Preview', cv2.imread(output_path))
        cv2.waitKey(0)
        cv2.destroyAllWindows()
    else:
        print("Error: Unable to save image file.")
binarize_image('/home/jetson/opencv/images/yahboom_logo.png', \
               '/home/jetson/opencv/images/yahboom_logo_binarize.png', \
               127)

Image grayscale conversion

Image edge detection