ADAPTIVE FINGERPRINT IMAGE ENHANCEMENT USING PROCESSING BLOCKS (original) (raw)

Adaptive fingerprint enhancement method is based on contextual filtering. Contextual filtering is a popular technique for fingerprint enhancement, where topological filter features are aligned with the local orientation and frequency of the ridges in the fingerprint image. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Fingerprint image enhancement is mainly used in ridge structure. Ridge structures in fingerprint images are not always well defined; therefore, enhancement algorithm is necessary .Two important ridge characteristics: Ridge ending, Ridge bifurcation. The adaptive fingerprint enhancement method comprises five processing blocks. 1) Pre-processing; 2) global analysis; 3) local analysis; and 4) matched filtering; 4) Image segmentation. In the pre-processing and local analysis blocks, a nonlinear dynamic range adjustment method, SMQT is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method.