Abstract: A fast local feature description algorithm is proposed in this paper based on the intensity distribution property of local neighbor, called normalized intensity contrast descriptor (NICD). After normalizing pixel intensity of local neighbor areas surrounding interest points, the descriptors could be computed based on the intensity distribution property of local neighbor. For evaluating the performance of NICD, we adopt three detectors: fast-Hessian, DoG, and Harris-Laplacian, with NICD respectively in image matching and object recognition test. The results of evaluations show that this new descriptor is competitive with the performance of SIFT descriptor and SURF descriptor in geometric and photometric deformations. However, the matching time is greatly shortened when using NICD. Therefore, NICD is more suitable in real-time applications.