Human Age Estimation based on Ear Biometrics using KNN

At Present, humans have several peculiar and exclusive biometrics characteristic features which help to distinguish as part of identification. Basically, biometrics diagnose the people by surveying few aspects of individual anatomy or physiology such as Face, Fingerprint, FKP, Palm print, iris, etc., Likewise the ear recognition system are considered to be the most powerful tool in forensic application. This work presents a detailed analysis of the extraction of soft biometrics traits such as age- gender from each individual which help in contributing several identification decisions by primary biometrics and also to improve the matching Performance. In this work age of several persons are trained from Ear dataset with Gabor feature extraction with the modified version of KNN and the results are evaluated with the Performance Examination based on matching ratio based on the comparison status with KNN.