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A Novel Feature Descriptor for Face Anti-Spoofing Using Texture Based Method

Open Access
|Sep 2020

Abstract

In this paper we propose a novel approach for face anti-spoofing called Extended Division Directional Ternary Co-relation Pattern (EDDTCP). The EDDTCP encodes co-relation of ternary edges based on the centre pixel gray values with its immediate directional neighbour and its next immediate average directional neighbour, which is calculated by using the average of cornered neighbours with directional neighbours. The proposed method is robust against presentation attacks by extracting the spatial information in all directions. Three Experiments were performed by using all the four texture descriptors (LBP, LTP, LGS and EDDTCP) and the results are compared. The proposed face anti-spoofing method performs better than LBP, LTP and LGS.

DOI: https://doi.org/10.2478/cait-2020-0035 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 159 - 176
Submitted on: Jan 5, 2020
Accepted on: Aug 7, 2020
Published on: Sep 13, 2020
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 R. J. Raghavendra, R. Sanjeev Kunte, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.