Global descriptors have the future of low dimension and simple similarity measurement.An improved global invariant is proposed based on the medial axis skeletons and geodesic distance for bending deformation.First

we use the geodesic distance to correct the image centroid

and then we extract the skeleton instead of the global image domain as operational point set to reduce the computational complexity. Finally

we propose single dimension invariants.The experimental results show that compared with other traditional feature representation the invariant is bending insensitive and meets the test of TRS(translation

rotation

scaling) invariance.It can effectively represent and identify bending non-rigid shapes.In this paper

we propose a novel global invariant of single dimension.Its simple structure makes it possible to use simple calculations to achieve real-time performance.This descriptor provides a new method to robustly identify objects with bending deformation.