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Preprocessing With Symmetrical Face And Gamma Correction For Face Recognition Under Varying Illumination With Robust Regression Classification

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Eva Y Puspaningrum Budi Nugroho Andri Istifariyanto

Abstract

Facial recognition is one of the most popular issues in the field of pattern recognition.
Face recognition with uncontrolled lighting conditions is more significant than the
physical characteristics of individual faces. Uncontrolled lighting from the right and left
can affect the face image. A lot of research on facial recognition, but little attention given
to the face image is symmetrical object. Several studies to explore and exploit the
symmetrical properties of the face for face recognition were performed. In this paper, we
propose a pre-processing method to solve one of the common problems in facial images
with varying illumination. We utilize the symmetric property of the face then performed
gamma correction then classified using Robust Regression. The results of this experiment
got an average accuracy of 94.31% and the proposed technique improves recognition
accuracy especially in images with extreme lighting conditions using gamma correction
parameters γ = 0.3.

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How to Cite
PUSPANINGRUM, Eva Y; NUGROHO, Budi; ISTIFARIYANTO, Andri. Preprocessing With Symmetrical Face And Gamma Correction For Face Recognition Under Varying Illumination With Robust Regression Classification. Jurnal Ilmiah Kursor, [S.l.], v. 9, n. 2, apr. 2018. ISSN 2301-6914. Available at: <http://kursorjournal.org/index.php/kursor/article/view/142>. Date accessed: 16 july 2018.
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