Although detecting text lines in machine printed documents is typically considered a solved problem, it is still a challenge to segment handwritten text lines in the general sense given no prior knowledge of script. This paper models text line detection as an image segmentation problem by enhancing text line structures using a Gaussian window and adopting the level set method to evolve text line boundaries. Experiments show that the method, which is script independent, achieves high accuracy for detecting text lines in heterogeneous handwritten documents.