An Efficient Coding Method for Indexing Hand-based Biometric Databases

Biometric identification systems capture biometric (i.e., fingerprint, palm, and iris) images and store them in a central database. During identification, the query biometric image is compared against all images in the central database. Typically, this exhaustive matching process (linear search) works very well for the small databases. However, biometric databases are usually huge and this process increases the response time of the identification system. To address this problem, we present an efficient technique that computes a fixed-length index code for each biometric image. Further, an index table is created based on the indices of all individuals. During identification, a set of candidate images which are similar to the query are retrieved from the index table based on the values of query index using voting scheme that takes a constant time. The technique has been tested on benchmark PolyU palm print database and NTU Vein pattern database. The technique performs with lower penetration rates for 100 % hit rate for both the databases. These results show a better performance in terms of response time and search speed compared to the state-of-the-art indexing methods.