A　gear　integrated　error,　a　combination　of　individual　and　composite　errors,　carries　richer　information　and　has　long　been　a　key　target　of　classic　gear　error　measurement　techniques.　However,　in　the　age　of　intelligent　manufacturing,　the　classic　methods　for　gear　integrated　error　measurement　are　no　longer　able　to　meet　the　emerging　requirements　of　large-scale　gears　and　real-time　online　measurement.　To　address　this　gap,　a　novel　approach　to　obtaining　the　gear　integrated　error　based　on　GTC-Facet　(Gaussian　template　convolution-Facet)　is　proposed.　This　method　accurately　pinpoints　the　sub-pixel　contour　of　gears　in　images,　enabling　a　quick　derivation　of　the　gear　integrated　error　curve.　From　this　curve,　other　individual　and　composite　errors　can　be　analyzed.　The　gear　error　information　obtained　through　our　method　has　higher　measurement　accuracy,　achieving　a　positioning　accuracy　of　3.6　mu　m　for　the　gear　profile.　Moreover,　during　the　measurement　process,　the　measured　gear　remains　unclamped,　and　the　entire　measurement　process　can　be　completed　within　0.35　s,　which　is　much　faster　than　classic　methods.　Our　method　meets　the　demands　of　online　measurements　and　provides　a　new　avenue　for　gear　error　measurement.