Detect clusters of circular objects by iterative adaptive thresholding and shape analysis

Question

I have been developing an application to count circular objects such as bacterial colonies from pictures.

What make it easy is the fact that the objects are generally w

Answer 1

Several years ago I wrote an aplication that detects cells in a microscope image. The code is written in Matlab, and I think now that is more complicated than it should be (it was my first CV project), so I will only outline tricks that will actually be helpful for you. Btw, it was deadly slow, but it was really good at separating large groups of twin cells.

I defined a metric by which to evaluate the chance that a given point is the center of a cell: - Luminosity decreases in a circular pattern around it - The variance of the texture luminosity follows a given pattern - a cell will not cover more than % of a neighboring cell

With it, I started to iteratively find the best cell, mark it as found, then look for the next one. Because such a search is expensive, I employed genetic algorithms to search faster in my feature space.

Some results are given below: