Genetic programming based image segmentation with applications to biomedical object detection

Image segmentation is an essential process in many image analysis applications and is mainly used for automatic object recognition purposes. In this paper, we define a new genetic programming based image segmentation algorithm (GPIS). It uses a primitive image-operator based approach to produce linear sequences of MATLAB® code for image segmentation. We describe the evolutionary architecture of the approach and present results obtained after testing the algorithm on a biomedical image database for cell segmentation. We also compare our results with another EC-based image segmentation tool called GENIE Pro. We found the results obtained using GPIS were more accurate as compared to GENIE Pro. In addition, our approach is simpler to apply and evolved programs are available to anyone with access to MATLAB®.