Image　segmentation　is　a　chief　and　basic　issue　in　the　field　of　image　analysis　as　well　as　pattern　recognition.　Meanwhile,　it　is　also　the　classical　puzzle　in　image　processing.　And　the　watershed　transform　is　a　powerful　morphological　tool　for　image　segmentation.　But　its　short-coming　is　to　cause　over-segmentation.　Therefore,　labeling　watershed　algorithm　has　been　presented　in　this　paper.　Firstly,　a　bilateral　filtering　is　applied　to　smooth　the　original　image,　so　it　can　reduce　part　of　noise.　Secondly,　according　to　the　characteristics　of　the　ore　image　the　distance　transform　and　morphological　reconstruction　are　used　to　realize　labeling　watershed　transformation　on　this　basis.　Finally,　segmentation　result　is　obtained　by　using　an　improved　method　of　labeling　watershed　algorithm.　The　experimental　result　shows　that　the　method　can　reduce　over-segmentation　more　efficiently,　with　a　precision　of　more　than　80%.　©　2011　IEEE.