The invention discloses a micro-groove feature segmentation method and system based on white light interferometry, and belongs to the field of image processing. Analysis of features of steps, transition areas, channels and noise in a micro-groove three-dimensional image shows that when two attributes of height and gradient are adopted for description, the interior of each feature is uniform and consistent, the difference between the features is large, and the attribute description between the features is basically not crossed, so that the accuracy of the feature description is greatly improved. According to the method, two parameters of height and gradient are used as two-dimensional attributes to describe each feature, so that the influence caused by noise can be avoided, and meanwhile, the distinguishing description capability on three to-be-extracted features of steps, transition regions and channels is relatively high; besides, a surface feature probability description method is adopted, automatic segmentation of groove microstructure features is realized based on a maximum information entropy principle, and height matrixes of various features for evaluation are obtained; the process does not need manual interference, the segmentation efficiency and accuracy are high, and the certainty is high.