A　method　combining　motion　image　deblurring　restoration　and　mechanical　de-vibrating　in　optical　flow　field　based　on　affine　motion　model　is　proposed　to　improve　the　accuracy　of　optical　flow　odometer　based　velocity　measurement　method　for　intelligent　wheelchair.　Large　wheelchair　translational　velocity　or　rotational　velocity　leads　to　significant　image　motion　blur　for　a　fast　moving　onboard　camera;　additionally,　the　mechanical　dithering　of　intelligent　wheelchair　robot　easily　deteriorates　the　quality　of　optical　flow　field;　both　of　which　affect　the　accuracy　of　velocity　estimation.　Aiming　at　this　problem,　a　motion　deblurring　method　based　on　adaptive　fuzzy　kernel　is　employed　in　this　paper　for　image　restoration　and　improving　the　quality　of　the　video　frames;　Secondly,　aiming　at　the　mechanical　vibration　in　the　moving　process　of　the　intelligent　wheelchair,　under　the　framework　of　Kalman　filter,　the　affine　motion　model　parameters　of　consecutive　image　pairs　are　estimated　with　the　optical　flow　field　vectors　refined　by　RANSAC　(Random　Sample　Consensus),　which　realizes　optical　flow　compensation　for　removing　the　mechanical　vibration.　Experiment　results　show　that　the　proposed　method　is　capable　of　improving　the　accuracy　of　visual　velocity　measurement　of　intelligent　wheelchair　based　on　optical　flow　field.　©　2016,　Science　Press.　All　right　reserved.