In　recent　years,　with　the　continuous　development　of　the　ceramic　industry,　the　problem　of　Product　defect　has　become　increasingly　prominent.　Therefore,　this　article　conducted　recognition　research　on　Dehua　porcelain　through　image　processing　technology.　Firstly,　the　background　and　research　significance　of　this　article　were　elaborated;　Secondly,　a　detailed　analysis　was　conducted　on　the　detection　technology　and　application　status　of　powder　and　particle　size　in　ceramic　processing;　Next,　the　principle　and　implementation　process　of　defect　recognition　based　on　machine　vision　were　elaborated,　and　experimental　results　were　compared　and　error　corrected.　At　the　same　time,　improved　algorithms　were　proposed　to　improve　identification　accuracy;　Finally,　this　paper　tests　the　performance　of　the　porcelain　Product　defect　recognition　model,　and　the　test　results　show　that　the　resource　occupancy　rate　of　this　model　is　between　2%　and　4%,　and　the　defect　recognition　rate　is　relatively　high,　which　can　meet　the　demand.　Compared　with　the　traditional　visual　inspection,　the　defect　recognition　method　based　on　image　processing　can　realize　the　automatic　detection　process.　It　can　improve　production　efficiency　and　reduce　the　impact　of　human　errors　and　subjective　judgments.　This　method　can　identify　the　defects　of　Dehua　porcelain　products　in　real　time　and　reduce　the　time　and　labor　cost　of　traditional　detection　methods.　©　COPYRIGHT　SPIE.