The comet assay is a commonly used technique in molecular and cell biology fields, for studies in which the DNA damage of a cell is measured. For instance, it is useful to analyze whenever a carcinogenic cell is affected by chemical agents, helping with oncology research. Traditionally, in order to evaluate the damage of a cell, an expert observes the morphology and the intensity (brightness) of the resulting comet. However, taking into account that a large number of images have to be analyzed, this task may demand a lot of time to be done manually. In recent years, the comet assay analysis has been implemented semi-automatically and automatically with the rise of new image processing algorithms. Although these new algorithms reduce the time invested in the image analysis, some problems in comet identification and accurate measure of their components need to be improved. This project aimed to develop an algorithm and an interface, named CometLab, for flexible automatic comet segmentation. Its performance was assessed with a set of images and compared against an open source, available software called OpenComet. It was found that only 1 of the 15 features that were extracted by both algorithms was not statistically correlated (head diameter), meaning that the designed application is suitable; therefore, this research helped to obtain information about the performance of CometLab in comparison to OpenComet, which serves as setpoint for future works in which it would be possible to decide which algorithm is better.