Computer Vision Demonstration Website

Electronics and Computer Science
University of Southampton

Laplacian & Marr Hildreth Edge Detection

Marr-Hildreth edge detection finds edges by second order differentiation. It also has the ability to detect edges at different scales, much like the human vision system.

How it works

Marr-Hildreth uses the Gaussian smoothing operator to improve the response to noise, and by differentiation the Laplacian of Gaussian is called the LoG operator.

Edges are at the 'zero crossings' of the LoG, which is where there is a change in gradient.

Code

Image processing classes:

• laplacian.java
• gaussianFilter.java

Noise generation classes:

• gaussianNoise.java
• condimentNoise.java

Demo framework:

• laplacianDemo.java

The pages were designed and developed for educational purposes only, to demonstrate how computer vision techniques work. They are designed for no other purpose and neither the authors nor their institutions accept any liability concerning use of these pages.

Links

Mark Nixon & Alberto Aguado, 2002, Feature Extraction & Image Processing, Newnes

ECS | Feature Extraction & Image Processing | © 2005 University of Southampton