The　algorithm　of　classification　is　one　of　the　important　problems　to　be　solved　in　the　field　of　chip　manufacturing,　which　has　a　great　impact　on　the　efficiency　of　process　such　as　subsequent　chip　packaging.　According　to　the　requirement　of　intelligent　control　of　chip　production　system,　chip　classification　algorithm　based　on　extreme　learning　machine　(ELM)　is　studied.　In　this　paper,　we　use　image　edge　gradient　information　as　feature　vector　and　use　ELM　to　classify　the　chip.　In　order　to　improve　the　speed　of　the　algorithm,　we　use　image　pyramid　to　down-sample　the　image　first.　The　final　experimental　results　show　that,　in　small-scale　testing,　our　algorithm　can　achieve　100%　accuracy　and　it　is　insensitive　to　illumination　changes.　When　the　image　rotates,　our　method　can　achieve　more　than　93.3%　accuracy.　©　2018　Association　for　Computing　Machinery.