Segmenting overlapped objects in images. A study to support the diagnosis of sickle cell disease

Overlapped objects are found on multiple kinds of images, they are a source of problem due its partial information. Multiple types of algorithm are used to address this problem from simple and naive methods to more complex ones. In this work we propose a new method for the segmentation of overlapped object. Finally we compare the results of this algorithm with the state-of-art in two experiments: one with a new dataset, developed specially for this work, and red blood smears from sickle-cell disease patients.