A　new　froth　collapse　rate　detection　method　by　the　fusion　of　fast　retina　keypoint(FREAK)　and　shape　omnidirectional　similarity　in　Nonsubsampled　Shearlet　transform(NSST)　multiscale　domain　was　proposed,　consi-dering　the　difficulty　to　detect　the　froth　collapse　rate　resulted　from　continuous　flow　and　movement　deformation.Firstly,　two　adjacent　froth　images　were　decomposed　through　NSST,　froth　bright　spots　are　extracted　by　segmentation　of　low　frequency　subband　image.And　feature　points　were　tested　by　direction　modulus　maxima　detection　and　nonmaximum　suppression　among　multiscale　high　frequency　subbands,　then　FREAK　sampling　pattern　was　improved　and　used　for　feature　points　description　and　matching.Secondly,　potential　collapsed　bubbles　were　extracted　according　to　the　number　of　matching　points　that　around　the　bright　spots　of　previous　frame,　and　then　collapsed　bubbles　were　selected　from　potential　collapsed　bubbles　by　using　shape　complexity　feature　and　omnidirectional　similarity　detection　of　bright　spots　between　previous　frame　and　next　frame.Finally,　the　bubble　collapse　rate　was　calculated　according　to　the　detection　results　of　collapsed　bubble.Experimental　results　show　that,　the　proposed　method　is　affected　little　by　nonuniform　flow　and　movement　deformation　of　bubbles　and　can　effectively　extract　all　collapsed　bubbles.Besides,　it　achieves　not　only　a　better　detection　accuracy　than　that　of　existing　methods,　but　also　robustness　of　performance　under　different　flotation　working　condition,　thus　this　method　meets　the　on-line　detection　need　of　flotation　production.　©　2020,　Editorial　Department,　Journal　of　South　China　University　of　Technology.　All　right　reserved.