IJBTT

Detection of Gender Using Digital Forensic
	© 2020 by IJCTT Journal
	Volume-68 Issue-3
	Year of Publication : 2020
	Authors : Aishwari Nandini Bishnu Rout, Shivali Pandit , Harshada Patil , Prof VijayKumar Patil
	DOI :  10.14445/22312803/IJCTT-V68I3P102

How to Cite?

Aishwari Nandini Bishnu Rout, Shivali Pandit , Harshada Patil , Prof VijayKumar Patil, "Detection of Gender Using Digital Forensic," International Journal of Computer Trends and Technology, vol. 68, no. 3, pp. 7-13, 2020. Crossref, 10.14445/22312803/IJCTT-V68I3P102

Abstract
A fingerprint is defined as a pattern present in between tips and joints of a finger. Fingerprint stays the same from the day of a person’s birth to the day they die. Fingerprints are found near crime sites, on weapons, in excavated things etc. Gender can be estimated on basis of features like ridge density patterns, some unique characters present in fingerprint and with the help of fingerprint patterns like loops, whorls, arches. Unknown fingerprint’s gender can be recognized. In the proposed system, different algorithms like Pre-processing, Image binarization, Thinning are used for feature extraction. This study proposes, a trained model using image classifier of fingerprint instead of traditional analysis. Our proposed System aims to determine gender using fingerprints. For an unknown fingerprint, different minutiae feature that are extracted basis on this decision can be taken whether it is male or female.

Keywords
CNN Classifier, Dactylography, Digital Forensic, Fingerprints, Image Processing, Minutiae Features.

Reference
[1] Nithin Mathew Sam, Rema P., Venugopalan Nair B,Study of Fingerprint Patterns in South Indian Population, Vol. 37, No. 4 , J Indian Acad Forensic Med. October-December 2015.
[2] S. S. Gornale, Basavanna M, Kruthi R, fingerprint based gender classification using minutiae extraction, Vol 6, No1 ,International Journal Of Advanced Research in Computer Science, 2010.
[3] Sandeep V. Binorkar1, Anand B. Kulkarni2, Study fingerprint pattern and gender distribution in and around Nanded district of Maharashtra state, DOI: 10.5455/ejfs.228851, European Journal of Forensic Sciences, 2016.
[4] Chandrakant P. Divate, Study of Different Bio-Metric Based Gender Classification Systems, DOI: 10.1109/ICIRCA.2018.8597340, International Conference on Inventive Research in Computing Applications (ICIRCA),2018.
[5] Nithin Mathew Sam, Study of Fingerprint Patterns in South Indian Population, DOI: 10.5958/0974-0848.2015.00096.2, Journal of Indian Academy Of Forensic Medicine, 2015.
[6] P. Gnanasivam and R. Vijayarajan, Gender classification from fingerprint ridge count and fingertip size using optimal score assignment, Complex & Intelligent Systems, 2018.
[7] Suman Sahu, A. Prabhakar Rao and Saurabh Tarun Mishra, Fingerprints based gender classification using Adaptive Neuro Fuzzy Inference System, 10.1109/ICCSP.2015.7322700, International Conference on Communications and Signal Processing (ICCSP),2015. Fig. 1. Magnetization as a function of applied field. Note that “Fig.” is abbreviated. There is a period after the figure number, followed by one space. It is good practice to briefly explain the significance of the figure in the caption. Fig. 1. Magnetization as a function of applied field. Note that “Fig.” is abbreviated. There is a period after the figure number, followed by one space. It is good practice to briefly explain the significance of the figure in the caption.
[8] Sudharshan Duth P, Megha P Mirashi, Fingerprint Based Gender Classification using ANN, Volume-8 Issue-5, International Journal of Engineering and Advanced Technology (IJEAT) ,2019.
[9] ImageNet (2016). About. [ONLINE] Available at: http://image-net.org/about- overview. [Accessed 20 April 2018].
[10] Gao, Y. and Mosalam, K. (2018). Deep Transfer Learning for Image-Based Structural Damage Recognition. Computer-Aided Civil and Infrastructure Engineering.
[11] Larsen-Freeman, D. (2013). Transfer of Learning Transformed. Language Learning, 63, pp.107-129.
[12] Alex Krizhevsky (2009). The CIFAR-10 dataset. [ONLINE] Available at: https://www.cs.toronto.edu/~kriz/cifar.html. [Accessed 20 April 2018].
[13] Vision Caltech (2018). Computational Vision. [ONLINE] Available at: http://www.vision.caltech.edu/html-files/archive.html. [Accessed 20 April 2018].
[14] Jianxin Wu, J. (2015). CNN for Dummies. Nanjing University.
[15] Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna (2016). Rethinking the Inception Architecture for Computer Vision. IEEE CVPR’16: Computer Vision and Pattern Recognition.
[16] Mathworks.com. (2018). Convolutional Neural Network. [online]Available https://www.mathworks.com/content/mathworks/www/en/discovery/convolution al-neural-network.html [Accessed 20 April 2018].
[17] Balaji V , Ajith Kumar P, Kiren Aananth A, Gunasekar N, Ciyamala Kushbu S “Forgery Detection in Documents” SSRG International Journal of Electronics and Communication Engineering, Volume 5 Issue 5 - May 2018.
[18] When and when is fingerprint analysis used?, http://www.forensicsciencesimplified.org/prints/why.html
[19] Applications, https://findbiometrics.com/applications/
[20] Mr. Vijaykumar N. Patil, Prof. Venkatesan N., “Securing Hadoop using OAuth 2.0 and Real Time Encryption Algorithm”, International Journal on Recent and Innovation Trends in Computing and Communication, Volume: 3 Issue: 7, ISSN: 2321-8169, pp-4382 – 4387
[21] Huma Jameel, Neelam Duhan, Sana Shakeel “Study of Cyberbullying Detection” SSRG International Journal of Computer Science and Engineering Volume 6 Issue 5 – May 2019.
[22] S.L.Jothilakshmi , K Valli , A.Vanitha , A. Selva nathiya , A.Shunmuga priya “Automatic Machine Learning Forgery Detection Based on SVM Classifier” SSRG International Journal of Mechanical Engineering, volume 1 Issue 1–Feb 2014.
[23] Mahbub Hussain, Jordan J. Bird, and Diego R. Faria, A study on CNN Transfer Learning for Image Classification, https://www.researchgate.net/publication/325803364, 2018.