Quantified　vibration　parameters　of　vocal　folds,　including　parameters　directly　extracted　from　high-speed　video　(HSV)　and　electroglottography　(EGG),　and　inverse　parameters　based　on　models,　can　accurately　describe　the　mechanism　of　phonation　and　also　classify　the　abnormal　in　clinics.　In　order　to　improve　the　reliability　and　accuracy　of　these　parameters,　this　paper　provides　a　method　based　on　an　integrated　recording　system.　This　system　includes　two　parts:　HSV　and　EGG,　which　can　record　vibration　information　of　vocal　folds　simultaneously.　An　image　processing　approach　that　bases　on　Zernike　moments　operator　and　an　improved　level　set　algorithm　is　proposed　to　detect　glottal　edges　at　subpixel-level　aiming　at　image　series　recorded　by　HSV.　An　approach　is　also　introduced　for　EGG　data　to　extract　three　kinds　of　characteristic　points　for　special　vibration　instants.　Finally,　inverse　parameters　of　vocal　folds　can　be　optimized　by　a　genetic　algorithm　based　on　the　experimental　vibration　behaviors　synthesized　with　these　parameters　and　the　simulations　of　a　two-mass　model.　The　results　of　a　normal　phonation　experiment　indicate　that　the　parameters　extracted　by　this　method　are　more　accurate　and　reliable　than　those　extracted　by　general　methods,　which　were　only　on　the　basis　of　HSV　data　and　with　pixel-level　processing　approaches　in　former　studies.