Image Processing with OpenCV

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It contains over 2500 optimized algorithms tailored for real-time computer vision applications.

To install OpenCV in Python, use the following command:

pip install opencv-python

Optionally, you can install additional modules:

pip install opencv-contrib-python

• Image Representation: Images are represented as multi-dimensional arrays.
• Color Spaces: Different ways to represent colors, e.g., RGB, HSV.
• Image Filtering: Techniques to enhance or detect features in images.

4.1 Reading and Displaying Images

import cv2

# Read an image
image = cv2.imread('path_to_image.jpg')

# Display the image
cv2.imshow('Image', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
                

4.2 Writing Images

# Save the image
cv2.imwrite('output_image.jpg', image)
                

5.1 Image Transformation

# Resize the image
resized_image = cv2.resize(image, (width, height))
                

5.2 Image Filtering

# Apply Gaussian Blur
blurred_image = cv2.GaussianBlur(image, (5, 5), 0)
                

• Use the latest version of OpenCV.
• Read the documentation for functions used.
• Always check for errors when reading/writing files.
• Utilize vectorized operations for performance.
• Keep your images organized and well-labeled.