The　rock　fracture　detection　by　image　analysis　is　significant　for　fracture　measurement　and　assessment　engineering.　The　paper　proposes　a　novel　image　segmentation　algorithm　for　the　centerline　tracing　of　a　rock　fracture　based　on　Hessian　Matrix　at　Multi-scales　and　Steger　algorithm.　A　traditional　fracture　detection　method,　which　does　edge　detection　first,　then　makes　image　binarization,　and　finally　performs　noise　removal　and　fracture　gap　linking,　is　difficult　for　images　of　rough　rock　surfaces.　To　overcome　the　problem,　the　new　algorithm　extracts　the　centerlines　directly　from　a　gray　level　image.　It　includes　three　steps:　(1)　Hessian　Matrix　and　Frangi　filter　are　adopted　to　enhance　the　curvilinear　structures,　then　after　image　binarization,　the　spurious-fractures　and　noise　are　removed　by　synthesizing　the　area,　circularity　and　rectangularity;　(2)　On　the　binary　image,　Steger　algorithm　is　used　to　detect　fracture　centerline　points,　then　the　centerline　points　or　segments　are　linked　according　to　the　gap　distance　and　the　angle　differences;　and　(3)　Based　on　the　above　centerline　detection　roughly,　the　centerline　points　are　searched　in　the　original　image　in　a　local　window　along　the　direction　perpendicular　to　the　normal　of　the　centerline,　then　these　points　are　linked.　A　number　of　rock　fracture　images　have　been　tested,　and　the　testing　results　show　that　compared　to　other　traditional　algorithms,　the　proposed　algorithm　can　extract　rock　fracture　centerlines　accurately.