Laplacian of Gaussian
Imagine you have a big, round balloon with some bumps on it. If you want to figure out how bumpy the balloon is, you could gently touch it all over with your fingers and try to feel the bumps. But what if you want to see the bumps instead of feeling them? That's where Laplacian of Gaussian comes in.
The Laplacian of Gaussian (LoG) is a special way of processing images to highlight the edges and corners of objects in it. It does this by taking the original image and smoothing it out, so it's like you're wrapping the balloon in some kind of stretchy material that smooths out all the bumps. Then, the LoG looks for places where the smoothness is suddenly interrupted, like where there is a corner or an edge in the image.
The LoG uses a mathematical formula to find these places where smoothness is interrupted. It's like a secret code that tells the computer where to look for edges and corners in the image. Once it finds these places, it marks them and makes them stand out more in the image. This makes it easier for humans to see where there are important features in the image.
To summarize, the Laplacian of Gaussian is a special way of processing images to highlight edges and corners. It does this by first smoothing out the image and then looking for places where the smoothness is interrupted. This helps make important features in an image easier to see.
The Laplacian of Gaussian (LoG) is a special way of processing images to highlight the edges and corners of objects in it. It does this by taking the original image and smoothing it out, so it's like you're wrapping the balloon in some kind of stretchy material that smooths out all the bumps. Then, the LoG looks for places where the smoothness is suddenly interrupted, like where there is a corner or an edge in the image.
The LoG uses a mathematical formula to find these places where smoothness is interrupted. It's like a secret code that tells the computer where to look for edges and corners in the image. Once it finds these places, it marks them and makes them stand out more in the image. This makes it easier for humans to see where there are important features in the image.
To summarize, the Laplacian of Gaussian is a special way of processing images to highlight edges and corners. It does this by first smoothing out the image and then looking for places where the smoothness is interrupted. This helps make important features in an image easier to see.