This project handles image processing for the underwater microscope. The purpose of the microscope is to take pictures of planktons – small creatures that lives underwater. Two main problems arose:
The microscope takes many pictures each second. As a result, in many pictures there are no planktons at all, or they’re size is negligible to the size of the background. In addition, the setup of the microscope caused the images to be with non-uniform illumination.
In order to make the pro-processing easier for marine biologists, there is a need to classify the images according to the plankton’s specie.
This project contains solutions for both of these problems. For the first one, we’ve managed to create an algorithm which identifies “interesting” parts in an image (not necessarily planktons), and gets good results even for pictures that contain more than one plankton. For the second problem we’ve created an algorithm that, in an unsupervised learning method, achieves 55% success in classification.