Human Age and Gender Determination Using Fingerprints

Open Access

Year : 2022 | Volume : | Issue : 2 | Page : 16-26

    Mukund Madhav

  1. Atrakesh Pandey

  1. Student, Department of Computer Science and Engineering, Poornima Institute of Engineering and Technology, Sitapura, Jaipur, Rajasthan, India


We present a review of technologies to determine human age and gender using fingerprints. Broadly two methodologies are reviewed i.e. Ridge based human age and gender determination and Image based human age and gender determination. Ridge based techniques uses ridge information with its variant statistics measures for classification of a human fingerprint into different classes of age groups and male/female distinction. These methods do not involve separate classifiers for classification rather determines different thresholds for different classes for classification. On the other hand, Image based techniques uses image processing concepts both in spatial and frequency domain like image transformation in frequency domain. These methods also need separate classifier like KNN (K-Nearest Neighborhood) classifier, SVM (Support Vector Machine) etc. to determine age and gender of a specific human fingerprint. Considering the two approaches different research papers are reviewed and their accuracy is stated for the difference. In the end advantages and disadvantages are concluded for both methodologies along with the future scope in this field.

Keywords: Fingerprints, ridge based classification, image based classification, KNN, SVM, gender determination

[This article belongs to Journal of Advancements in Robotics(joarb)]

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1. Davide Maltoni, Dario Maio, Anil K. Jain and Salil Prabhakar. “Handbook of Fingerprint Recognition.” ISBN 0-387-95431-7, 2003-Springer-Verlag New York, Inc.
2. Sheetlani, Jitendra, and Rajmohan Pardeshi. “Fingerprint based automatic human gender identification.” Int. J. Comput. Appl 170.7 (2017): 1–4.
3. Bergstrom, Brittni Elizabeth. “Effect of Speaker Age and Dialect on Listener Perceptions of Personality.” (2017).
4. Falohun, A.S., O.D. Fenwa, and F.A. Ajala. “A Fingerprint-based Age and Gender Detector System using Fingerprint Pattern Analysis.” International Journal of Computer Applications 136.4 (2016): 0975–8887.
5. Abdullah, S.F., et al. “Development of a Fingerprint Gender Classification Algorithm Using Fingerprint Global Features.” International Journal of Advanced Computer Science and Applications (IJACSA) 7.6 (2016).
6. Ritika Dadhwal and Ajmer Singh. “Comparison Between Feature Extraction Techniques For Fingerprint Based Gender Classification Using KNN Classifier. Int.J.Computer Technology & Applications (IJCTA), 9 (11) 2016, pp. 5419–5426.
7. Champod, Christophe, et al. Fingerprints and other ridge skin impressions. CRC press, 2017.
8. Bawolek, Edward John, and Douglas E. Loy. “Method and apparatus for capture of a fingerprint using an electro-optical material.” U.S. Patent Application No. 15/821,942.
9. Bawolek, Edward John, and Douglas E. Loy. “Method for recording a fingerprint image.” U.S. Patent Application No. 16/535,209.
10. Alok Chauhan, Akhil Anjikar, Suchita Tarare. “Study of Ridge Based and Image Based Approach for Fingerprint Gender Classification.” International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE) Vol. 3, Issue 3, March 2015.
11. Doroz, Rafal, Krzysztof Wrobel, and Piotr Porwik. “An accurate fingerprint reference point determination method based on curvature estimation of separated ridges.” International Journal of Applied Mathematics and Computer Science 28.1 (2018): 209–225.
12. Thirumoorthi, C. “Fingerprint Based Authentication Using Image Processing Techniques.” (2018).
13. Suwarno, Sri, and P. Insao Santosa. “Short Review of Gender Classification based on Fingerprint using Wavelet Transform.” IJACSA 8.11 (2017).
14. Patil, Abhijit, R. Kruthi, and Shivanand Gornale. “Analysis of multi-modal biometrics system for gender classification using face, iris and fingerprint images.” International Journal of Image, Graphics and Signal Processing 11.5 (2019): 34.
15. Wedpathak, Mr GS, et al. “Fingerprint Based Gender Classification Using ANN.” International Journal of Recent Trends in Engineering & Research 4.3 (2018): 72–75.
16. Champod, Christophe, et al. Fingerprints and other ridge skin impressions. CRC press, 2017.
17. Shaik, Subhani, and Anto A. Micheal. “Automatic age and gender recognition in human face image dataset using convolutional neural network system.” International Journal of Advance Research in Computer Science and Management Studies 4.2 (2016).
18. Kumar, Sandeep, Sukhwinder Singh, and Jagdish Kumar. “A study on face recognition techniques with age and gender classification.” 2017 International Conference on Computing, Communication and Automation (ICCCA). IEEE, 2017.
19. Azam, Samiul. Visual Aesthetics for Person Identification and Gender Recognition. MS thesis. Graduate Studies, 2017.
20. Gier, Vicki S., and David S. Kreiner. “Recognizing a missing senior citizen in relation to experience with the elderly, demographic characteristics, and personality variables.” Current Psychology (2019): 1–16.
21. Gnanasivam, P., and Dr S. Muttan. “Fingerprint gender classification using wavelet transform and singular value decomposition.” arXiv preprint arXiv:1205.6745 (2012).
22. Gnanasivam, P., “Gender Classification and Age Estimation Using Fingerprint and Ear Features.” Doctor of Philosophy, August 2014, Faculty of Information and Communication Engineering, Anna University, Chennai.
23. Gnanasivam, P., and Dr S. Muttan. “Estimation of age through fingerprints using wavelet transform and singular value decomposition.” International Journal of Biometrics and Bioinformatics (IJBB) 6.2 (2012): 58–67.
24. T. Arulkumaran, Dr. P.E. Sankara Narayan anand, Dr. G. Sundari. “Fingerprint Based Age Estimation Using 2D Discrete Wavelet Transforms and Principal Component Analysis.” International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREEIE) Vol. 2, Issue 3, March 2013.

Regular Issue Open Access Article
Volume 9
Issue 2
Received August 10, 2021
Accepted August 30, 2022
Published September 17, 2022