The　ice　cream　stick　is　a　kind　of　wood　product　with　a　plane　surface.　For　the　qualified　stick　it　has　the　nearly　flat　surface.　However,　due　to　slender　and　thin　shape　the　bend　defect　is　prone　to　occur　during　machining　of　ice　cream　stick.　At　present,　manual　technique　is　often　used　to　identify　the　bend　defect　in　the　industrial　fields,　which　holds　many　problems　such　as　low　efficiency,　low　automation　and　unreliable　detection　result.　In　the　paper,　the　PCA-based　bend　feature　selection　method　is　proposed　which　is　applied　in　defect　detection　of　ice　cream　stick.　At　first,　the　3D　data　of　object　surface　is　obtained　based　on　the　three-dimensional　(3D)　measurement　principle　of　line　structured　light.　Then　four　kinds　of　bend　features　are　designed　according　to　the　shape　characteristics　of　the　light　stripe,　which　include　variation　coefficient,　correlation　coefficient,　determination　coefficient　and　straightness　metric.　At　last,　the　bend　feature　selection　is　operated　based　on　the　PCA-based　method.　The　research　results　provide　valuable　reference　for　the　engineering　application　in　the　intelligent　defect　detection.　©　2022　SPIE.