Authentication through gender classification from iris images using support vector machine
- 14 May 2021
- journal article
- research article
- Published by Wiley in Microscopy Research and Technique
- Vol. 84 (11), 2666-2676
- https://doi.org/10.1002/jemt.23816
Abstract
Soft biometric information, such as gender, iris, and voice, can be helpful in various applications, such as security, authentication, and validation. Iris is secure biometrics with low forgery and error rates due to its highly certain features are being used in the last few decades. Iris recognition could be used both independently and in part for secure recognition and authentication systems. Existing iris-based gender classification techniques have low accuracy rates as well as high computational complexity. Accordingly, this paper presents an authentication approach through gender classification from iris images using support vector machine (SVM) that has an excellent response to sustained changes using the Zernike, Legendre invariant moments, and Gradient-oriented histogram. In this study, invariant moments are used as feature extraction from iris images. After extracting these descriptors' attributes, the attributes are categorized through keycode fusion. SVM is employed for gender classification using a fused feature vector. The proposed approach is evaluated on the CVBL data set and results are compared in state of the art based on local binary patterns and Gabor filters. The proposed approach came out with 98% gender classification rate with low computational complexity that could be used as an authentication measure.Keywords
This publication has 57 references indexed in Scilit:
- Investigating the potential of Zernike polynomials to characterise spatial distribution of macular pigmentPLOS ONE, 2019
- Human Behavior Analysis Based on Multi-Types Features Fusion and Von Nauman Entropy Based Features ReductionJournal of Medical Imaging and Health Informatics, 2019
- CVBL IRIS Gender Classification Database Image Processing and Biometric Research, Computer Vision and Biometric Laboratory (CVBL)Published by Institute of Electrical and Electronics Engineers (IEEE) ,2018
- Iris or Periocular? Exploring Sex Prediction from Near Infrared Ocular ImagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Machine aided malaria parasitemia detection in Giemsa-stained thin blood smearsNeural Computing & Applications, 2016
- Exploring Gender Prediction from Iris BiometricsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Data Hiding Based on Improved Exploiting Modification Direction Method and Huffman CodingJournal of Intelligent Systems, 2014
- Invariant Scattering Convolution NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence, 2013
- SVM Based Gender Classification Using Iris ImagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2012
- Histograms of Oriented Gradients for Human DetectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005