Hybrid HOG-SVM encrypted face detection and recognition model

Title

Hybrid HOG-SVM encrypted face detection and recognition model

Creator

Sharma S.; Raja L.; Bhatnagar V.; Sharma D.; Bhagirath S.N.; Poonia R.C.

Description

Security plays a major role in an individuals life to win this world with highly secure and authentic lifestyle with the digital equipments. The paper proposed an encryption based secure face detection and recognition model which can be implemented in daily life to generate a more robust and efficient security bubble around the world. The most crucial problem encountered during face recognition is due to the variation in face direction of an individual, the model solves the mentioned pose variation problem. The proposed model takes the help of face recognition library to recognize the face and use HOG (Histogram of Oriented Gradients) & SVM for checking the face authentication by performing an image match, the model also applies the concept of HOG to generate the encoded features from the image. The system is divided into two modules first is to detect a face and then match the detected face from the authentic persons dataset available. The system uses the concept of OpenCV library for giving a support system for the real time image. For data encryption, proposed model used the concept of DES3 and RSA algorithm. The proposed model gets 83.33% accuracy while tested for three different image types and states that the RSA algorithm performs encryption in less computational time. 2022 Taru Publications.

Source

Journal of Discrete Mathematical Sciences and Cryptography, Vol-25, No. 1, pp. 205-218.

Date

2022-01-01

Publisher

Taylor and Francis Ltd.

Subject

68M25; DES3; Face landmark estimation; HOG; RSA; SVM

Coverage

Sharma S., Department of Computers Applications, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Raja L., Department of Computers Applications, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Bhatnagar V., Department of Computers Applications, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Sharma D., Department of Computers Applications, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Bhagirath S.N., Department of Computers Applications, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India; Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India

Rights

Restricted Access

Relation

ISSN: 9720529

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.1080/09720529.2021.2014141

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122342129&doi=10.1080%2f09720529.2021.2014141&partnerID=40&md5=7ce27d833acb9db95aac8e9442d57620