Fingerprint Based Age Estimation Obtained through 2D DWT, PCA and SVM

Fingerprints are the most widely used proofs for identifying the individual. fingerprint evidence is undoubtedly the most reliable and acceptable evidence till date in the court of law. Fingerprints are obtained at the site of crime and in many old monuments and in excavated things. In this work, we used human fingerprints as an evidence to determine the human age. Estimating the age of the fingerprints is an emerging field and many methods using the fingerprint physical features like the ridge count and the ridge thickness have been used so far. Due to the limitless potential of fingerprints as an effective method of identification an attempt has been made in the present work to analyze their correlation with age of an individual using frequency domain technique and a pattern recognition technique. Encouraged by the fact that human fingerprint differs in width ranging from birth to middle age but patterns remain unchanged. The combined processing has provided better results. This paper aims in using 2D- Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) combined to estimate a person’s age using an obtained fingerprint. The Support Vector Machine (SVM) is used as a classifier. The obtained fingerprint image goes through two steps of feature extraction process and results in separate feature vectors which are then combined to produce a final future vector. The Support Vector Machine (SVM) was used as a classifier. 120 Fingerprints belonging to the various ages in between 1 –60 were taken for analysis. The experimental results show good for trained database. It was found that increasing the database population in each category improves the performance of the system. This method can be useful in crime investigations to reduce the search space of suspects.