COMPARISION BETWEEN NEURAL NETWORK AND ADAPTIVE NEURO- FUZZY INFERENCE SYSTEM(ANFIS) RESULTS IN DETERMINATION OF GENDER USING FINGERPRINTS
Sahu, Suman, A. Prabhakar Rao, Saurabh Tarun Mishra · 2019
This research represents a novel identification of gender by using different features of fingerprints. Fingerprints are the biometric system provides an automatic recognition of an individual based on some unique features of an individual. Gender classification using fingerprints can be done by using spatial domain approach or frequency domain approach or it can be also done using the combination of both spatial domain and frequency approaches both. The identification and classification of fingerprints are based on feature extraction. In a fingerprint pattern , it consists of a number of Ridges and valleys presents in it. These makes different kind of structures on a fingerprint pattern, which are used for the identification of an individual. Cause each and every fingerprints are unique in the world. For the identification and classification, different algorithms are presented earlier. These algorithms are able to produce different recognition rates. However proposed results have usually been produced under fanamable conditions and technology.In this paper we have proposed the gender classification by using two methods NN and ANFIS and compare their results.