Image Analysis & Machine Learning

About

This web page gives an overview of the image analysis research conducted at HIOF. Traditional image analysis employed a formal approach to the problem, but today it is common to incorporate machine learning techniques to improve the performance.

Our research is focused on employing state-of-the-art machine learning techniques to improve on existing image analysis algorithms. See the links in the menu on the left for more information.

Publications

• Improving Graph-based Image Segmentation Using Automatic Programming Published at EvoIASP 2014.
• Edge Pixel Classification Using Automatic Programming Published at NIK 2014.
• Improving the Canny Edge Detector Using Automatic Programming: Improving The Filter Published at GECCO 2016.
• Improving the Canny Edge Detector Using Automatic Programming: Improving Non-Max Suppression Published at GECCO 2016.
• Improving the Canny Edge Detector Using Automatic Programming: Improving Hysteresis Thresholding Published at NIK 2016.