Fingerprint Image Compression using Retain Energy (RE) and Number of Zeros (NZ) through Wavelet Packet (WP)

Fingerprint analysis plays crucial role in crucial legal matters such as investigation of crime. But a fingerprint image consists of enormous amount of data. Therefore we have to reduce the amount of its data. To do this, we need some powerful image compression technique. There are many image compression techniques available, but still there is need to develop faster, and efficient and reliable techniques to compress fingerprint images. The main difficulty in developing compression algorithms for fingerprint is the need for preserving the minutiae i.e. ridges endings and bifurcations, which are subsequently used in identifications. To achieve high compression ratios while retaining these fine details, wavelet packets are used. In this paper we have done experimental analysis to determine compression ratio by Wavelet packet. We have used three wavelet transforms to select their threshold values and to calculate Retain Energy (RE) and Number of Zeros (NZ) in percentage. We have applied Haar; Daubechies (db1) and Symlet (sym2) transforms for noisy and noiseless fingerprint image of size 374 x 388 and determined their compression ratio. All these transforms give higher compression ratio for a noiseless fingerprint image than, noisy one.