A method that includes receiving a set of one or more images, each having one or more sets of pixels, receiving a ground truth value that a vertex point associated with a transition between two regions in a respective set of pixels, identifying a machine placement candidate vertex point for a first set of pixels, determining a set of one or more selected candidate features in the set of candidate features that maximizes an objective function that identifies an accuracy of the identified machine placement candidate vertex point compared to the respective ground truth for a respective set of pixels, updating a set of one or more basis features by adding the set of one or more selected candidate features that maximizes the objective function, and training a machine learning model based on the updated set of one or more basis features to identify additional vertex points for a transition.