Survey on Parameters of Fingerprint Classification Methods Based On Algorithmic Flow

Classification refers to assigning a given fingerprint to one of the existing classes already recognized in the literature. A search over all the records in the database takes a long time, so the goal is to reduce the size of the search space by choosing an appropriate subset of database for search. Classifying a fingerprint images is a very difficult pattern recognition problem, due to the minimal interclass variability and maximal intraclass variability. This paper presents a sequence flow diagram which will help in developing the clarity on designing algorithm for classification based on various parameters extracted from the fingerprint image. It discusses in brief the ways in which the parameters are extracted from the image. Existing fingerprint classification approaches are based on these parameters as input for classifying the image. Parameters like orientation map, singular points, spurious singular points, ridge flow, transforms and hybrid feature are discussed in the paper.