Statistical methods for automatic interpretation of digitally scanned finger prints

Orientation flow field is the starting point for feature extraction in various fingerprint algorithms. In recent papers, Jain and his colleagues (Ratha et al., 1995, Karu and Jain, 1995, Ratha et al. 1996) introduced a fundamentally new algorithm. Their main motivation for the algorithm has been to work at the problems from a fingerprint matching point of view. Our aim in contrast has been feature extraction from a dermatoglyphic point of view. Thus, we are not only interested in classification of the fingerprints but also other features such as ridge counts (number of ridges between any two points, say core points and tri-radius) and the average width of ridges in a region of fingerprint (see Loesch, 1983). Our end product is calculation of quantitative features rather than identification. Again, manual calculations of such quantities is a highly tedious task. We use some advanced techniques of spatial statistics, directional data analysis and Bayesian image analysis to obtain the orientation field. The algorithm is used to extract various features of interest from fingerprints.