Normalization of Facial Occlusion in Face Recognition
Tashev Komil Akhmatovich1, Khudoykulov Zarif Turakulovich2, Islomov Shahboz Zokir ugli3, Salimova Husniya Rustamovna4

1Tashev Komil Akhmatovich, Vice Rector for Scientific Affairs, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Uzbekistan.
2Khudoykulov Zarif Turakulovich, head of the Cryptology department, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Uzbekistan.
3Islomov Shahboz Zokir ugli, Phd student of the Cryptology department, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, Uzbekistan.
4Salimova Husniya Rustamovna, student of the Department of Computer engineering, Tashkent university of information technologies, Tashkent, Uzbekistan.

Manuscript received on 25 August 2019. | Revised Manuscript received on 03 September 2019. | Manuscript published on 30 September 2019. | PP: 2523-2527 | Volume-8 Issue-11, September 2019. | Retrieval Number: K17540981119/2019©BEIESP | DOI: 10.35940/ijitee.K1754.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Face recognition accuracy is determined by face detection results. Detected faces will be in view of clear and occlusion faces. If detected face has occlusion than recognition accuracy is reduced. This research is directed to increase recognition rate when detected occlusion face. In this paper is proposed normalization occlusion faces by Principal component analysis algorithm. After applying normalization method in occlusion faces false reject error rate is decreased.
Keywords: Face recognition, Occlusion, Face normalization, Deep learning, Error, Eigenvector, Eigenvalue, Average matrix.
Scope of the Article: Image Processing and Pattern Recognition