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Background/Objective: A computer based biological recognition system implementation for gender identification by using digitally acquired fingerprint through an optical fingerprint sensor. Methods/Statistical Analysis: Gender identification from fingerprint using Discrete Wavelet Transform and Principle Component Analysis for extracting both spatial domain features(SDF) and frequency domain features(FDF), and is combined together for accurate gender identification through a comparison with a set of sample fingerprints of different sex, age, ethnicity, etc. Findings: The results of this approach has revealed that the accuracy of the system depends on the database fingerprint images, bigger the database, better the results, wider the age range of the fingerprints in database, better the results, it also reveals, that unlike the traditional fingerprint ridge to valley thickness ratio methods, the computer based system is more accurate, faster and involves much less human effort, thereby avoiding human errors. Applications/Improvements: This system has a wide scope in anthropology, criminal investigations, personal identification systems like AADHAAR, etc. For large scale applications, a separate algorithm has to be developed for storing the feature vectors of the large amount of database images and significantly improve the processing speed.

Keywords

Discrete Wavelet Transform, Frequency Domain Features (FDF), Principle Component Analysis, Spatial Domain Features (SDF).
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