ASF-LLRDA: Locality-regularized Linear Regression Discriminant Analysis with Approximately Symmetrical Face Preprocessing for Face Recognition

Arya Widyadhana, Shintami Chusnul Hidayati*, Dini Adni Navastara, Yeni Anistyasari

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Face recognition is a crucial task in numerous applications, but it has difficulties because of the high-dimensional nature of facial photos, limited sample sizes, variations in illumination, and facial expressions. This paper presents a novel face recognition approach to overcome these challenges by combining the advantages of the Approximately Symmetrical Face (ASF) preprocessing strategy and the Locality-regulated Linear Regression Discriminant Analysis (LLRDA) method. The proposed method, called ASF-LLRDA, makes use of ASF to generate axis-symmetric face images for reducing the impact of illumination and variations in facial expressions, followed by LLRDA to extract discriminative features and project the data into a lower dimensional space. Locality-regulated Linear Regression (LLRC) is further utilized as the classifier. Experimental results on the Yale-B face dataset demonstrated the superiority of the proposed method compared to the baselines.

Original languageEnglish
Title of host publication2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2031-2036
Number of pages6
ISBN (Electronic)9798350300673
DOIs
Publication statusPublished - 2023
Event2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023 - Taipei, Taiwan, Province of China
Duration: 31 Oct 20233 Nov 2023

Publication series

Name2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023

Conference

Conference2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023
Country/TerritoryTaiwan, Province of China
CityTaipei
Period31/10/233/11/23

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