Total views : 249
Implementation of Biological Recognition System for Gender Identification using Fingerprint Images
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.
Discrete Wavelet Transform, Frequency Domain Features (FDF), Principle Component Analysis, Spatial Domain Features (SDF).
- Indira KP, Hemamalini RR, Indhumathi R. pixel based medical image fusion techniques using discrete wavelet transform and stationary wavelet transform. Indian Journal of Science and Technology. 2015; 8(26):1–7.
- Ganesh SS, Mohanaprasad K, Karuna Y. Object identification using wavelet transform. Indian Journal of Science and Technology. 2016; 9(5):1–7.
- Anilkumar PH, Beulet PAS. Lifting-based discrete wavelet transform for real-time signal detection. Indian Journal of Science and Technology. 2015; 8(25):1–6.
- Kumar A, Ghrera SP, Tyagi V. Modified buyer seller watermarking protocol based on discrete wavelet transform and principal component analysis. Indian Journal of Science and Technology. 2015; 8(35):1–9.
- Jhingan A, Kansal L. Performance evaluation for wavelet based Ofdm system effected by Cfo over Rayleigh channel. Indian Journal of Science and Technology. 2016; 9(5):1–6.
- Rajesh DG, Punithavalli M. An efficient fingerprint based gender classification system using dominant un-decimated wavelet coefficients. Research Journal of Applied Sciences, Engineering and Technology. 2014; 8(10):1259–65.
- Gornale SS, Geetha C, Kruthi R. Analysis of fingerprint image for gender classification using spatial and frequency domain analysis. American International Journal of Research in Science, Technology, Engineering & Mathematics (AIJRSTEM); 2013. p. 46–50.
- Anjikar A, Tarare S, Goswami MM. Fingerprint based gender classification using block-based DCT. International Journal of Innovative Research in Computer and Communication Engineering. 2015 Mar; 3(3):86–93.
- Kaur R, Mazumdar SG, Bhonsle D. A study on various methods of gender identification based on finger prints. in the International Journal of Emerging Technology and Advanced Engineering. 2012 Apr; 2(4):532–7.
- Chand P, Sarangi SK. A novel method for gender classification using DWT and SVD techniques. International Journal for Computer Technology and Applications. 4(3):445–9.
- Anjikar A, Tarare S, Goswami MM. Fingerprint based gender classification using block-based DCT. International Journal of Innovative Research in Computer and Communication Engineering. 2015 Mar; 3(3):1611–18.
- Tom RJ, Arulkumaran T. Fingerprint based gender classification using 2D discrete wavelet transforms and principal component analysis. International Journal of Engineering Trends and Technology. 2013; 4(2):199–203.
- Gnanasivam P, Muttan S. Fingerprint gender classification using wavelet transform and singular value decomposition. International Journal of Computer Science and Informatics. 2012; 1858:1–9.
- Reddy GG. Finger dermatoglyphics of the Bagathas of Araku Valley (A.P.). American Journal of Physical Anthropology. 1975; 42(2):225–8.
- Badawi, Mahfouz M, Tadross R, Jantz R. Fingerprint-based gender classification. Proceedings of the International Conference on Image Processing, Computer Vision and Pattern Recognition (IPCV’06); 2006 Jun. p. 41–6.
- Bhavani M, Rani S. Human identification using finger and iris images. International Journal of Computer Trends and Technology. 2013; 4(3).
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.