Image Edge Detection with OpenCV

Level: Real-World

Project Description

Image processing with OpenCV is the topic of today. For this project, we use Python for edge detection. Edge detection is an image processing technique used to identify boundaries or "edges" within an image. These edges represent points where the intensity of the image changes dramatically, such as transitions from light to dark areas, and often correspond to the outlines of objects or regions of interest. This technique is useful in real-world applications such as x-raying, self-driving cars, robotics, etc.

How the Project Works

The program reads the following PNG file:

Then, it uses Gaussian blurring via the OpenCV library to smooth out noise for more accurate results. Then, it applies canny edge detection. Finally, we use the matplotlib library to display the result which should be approximately as follows:

Prerequisites

Required Libraries: cv2, matplotlib
Installation: pip install opencv-python matplotlib
Required Files: Download the required files in the “Before Coding” section.
IDE: You can use any IDE on your computer to code the project.

Danger Zone

Here is the code solution: