A　2-D　image-processing　displacement-measuring　system　was　developed　to　provide　improved　measurements.　The　system　uses　nonlinear　mapping　calibration　algorithms,　such　as　a　back　propagation　(BP)　artificial　neural　network(ANN)　method,　least　square　(LS)　method,　and　an　combined　algorithm　(GA-LS)　from　the　genetic　algorithm　(GA)　and　LS,　in　a　Microsoft　Visual　Studio　integrated　development　environment.　The　system　was　used　to　analyze　the　factors　influencing　displacement　measurements.　The　results　show　that　the　cubic　surface　fitting　based　on　the　LS　method　is　the　best　among　the　3　calibration　algorithms.　Better　measurements　can　be　obtained　with　a　smaller　image　(but　larger　than　408　×　306　pixels),　larger　templates　for　smoothing　(but　less　than　1/2　of　a　marking　point　diameter)　and　for　opening　operations　(but　less　than　2/3　of　the　marking　point　diameter).　The　measuring　system　is　flexible　and　accurate　and　can　be　used　in　real-time.