An efficient indexing scheme for face database using modified geometric hashing

This paper presents an efficient scheme to index the database of facial images. It has made use of the modified geometric hashing technique. It uses minimum amount of search space and memory to provide top best matches with high accuracy against a query image. Control points are extracted using Speeded-Up Robust Feature points (SURF) operator. A pre-processing technique consisting of mean centring, principal components, rotation and normalization has been proposed to make these control points invariant to translation, rotation and scaling. The modified geometric hashing is used to hash these control points to index of the hash table. The indexing scheme has been tested on FERET face database which has achieved 100% hit rate for top 4 best matches.