This research work aims to characterize the algal colonization of mortar surfaces using image analysis. Theresistance of mortars to the biofouling is studied by means of an accelerated lab-scale test. A suspension of green algae Klebsormidium flaccidum, was performed to periodically sprinkle the mortar surfaces and digitalimages were acquired thanks to a scanner. The colonization rate of the surface follows a sigmoid type curve asa function of time that can be modeled thanks to Avrami’s model. It is described by a two-process mechanism:attachment and growth of algal stains. To identify the parameters of the algal colonization model, the imageswere segmented thanks to a random forest algorithm to obtain pixel information on the presence of algae.These processes were then represented with a morphological min-tree and information such as the number ofnew germs or their growth have been exploited to feed the Avrami’s model. The results show a good agreementbetween the modeling and the experimental data.