Methods of automatically extracting rock discontinuity data from three-dimensional surface models generated using current laser scanning technology are under development. Algorithms for the processing of raw point clouds, created by laser scanning exposed rock surfaces, have been developed. A novel method of triangular mesh generation rapidly creates a three-dimensional model of the scanned surface. The triangular elements of the mesh are grouped together using their normals as a similarity measure, resulting in the identification of larger fracture patches that represent discontinuity surfaces. A field study conducted at a rock cut along the Catalina Highway in Tucson, Arizona suggests that the discontinuity data collected from three-dimensional images, i.e., point clouds, compares favorably to data collected using more traditional manual field mapping methods. Additionally, a much more exhaustive data set is gathered and is done so without bias. Refinement and validation of this process has been initiated through a series of supplementary field studies. Additional algorithms that expand the application of automated rock mass characterization using three-dimensional laser scans are under development. The optimization of algorithms capable of processing three-dimensional data, finding and identifying discontinuities, and determining information such as fracture orientation, length, and spacing, will reduce the time required for data collection, eliminate human bias, make it possible to collect data from inaccessible rock faces, provide rapid data processing, and produce a more comprehensive database of discontinuity information.