The Importance of Blurring in Computer Vision Algorithms

Computer vision algorithms, especially those that perform real-time monitoring, are a very rich source of information with vital applications in everyday tasks like security or public place monitoring. However, a dilemma arises in monitoring people without exposing them to legal problems.

A simple solution to this issue is blurring people’s images to monitor them in real-time while maintaining their privacy.

The OpenCV library offers various image processing filters for pre-processing steps, including the ‘blur’ filter (cv2.blur()) method that smoothes images using a normalized box filter.

By utilizing the ‘blur’ filter, we can effectively blur images during object inference, ensuring privacy while monitoring individuals. The kernel used for blurring is represented as K, with a tuple ksize determining the kernel’s size.