Create a computer vision system using decision tree algorithms to solve a real-world problem : [Activity] Convolutions -

This lecture covers the application of convolution techniques in image processing, focusing on blurring and sharpening. It begins with importing necessary libraries like Matplotlib and OpenCV, followed by loading and displaying an image. The lecture then demonstrates converting a colored image to grayscale and applying sharpening and blurring kernels. The importance of kernel normalization is highlighted to ensure accurate image processing results. The session concludes with a recap of the key concepts discussed.

What steps are taken to visualize the sharpened image after applying the sharpening kernel?

How does increasing the size of the kernel affect the blurring effect on an image?

Summarize the key points covered in the lecture regarding convolutions and image processing.