International Research Journal of Computer Science (IRJCS) ISSN: 2393-9842
Issue 04, Volume 6 (April 2019) www.irjcs.com
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FACE RECOGNITION WITH OR WITHOUT MAKEUP
USING HAAR CASCADE CLASSIFIER ALGORITHM AND
LOCAL BINARY PATTERN HISTOGRAM ALGORITHM
Anna Liza A.Ramos Dania May P.Aguila Anne Catlyne B.Karunungan
Saint Michael’s College of Laguna Saint Michael’s College of Laguna Saint Michael’s College of Laguna
Binan City, Laguna, Philippines Binan City, Laguna, Philippines Binan City, Laguna, Philippines
annakingramos@yahoo.com.ph ; dmpaguila16@gmail.com ; akarunungan14@gmail.com
Jon-Jon B.Patiño Vincent L.Polintan
Saint Michael’s College of Laguna Saint Michael’s College of Laguna
Binan City, Laguna, Philippines Binan City, Laguna, Philippines
jonjonpatino@gmail.com ; vincentpolintaners@gmail.com
Manuscript History
Number: IRJCS/RS/Vol.06/Issue04/APCS10094
Received: 13, March 2019
Final Correction: 21, April 2019
Final Accepted: 26, April 2019
Published: April 2019
Citation: A.Ramos, P.Aguila, B.Karunungan, B.Patiño & L.Polintan (2019). Face Recognition with or without
makeup using HAAR Cascade Classifier Algorithm and local Binary Pattern Histogram Algorithm. IRJCS::
International Research Journal of Computer Science, Volume VI, 193-200. doi://10.26562/IRJCS.2019.APCS10094
Editor: Dr.A.Arul L.S, Chief Editor, IRJCS, AM Publications, India
Copyright: ©2019 This is an open access article distributed under the terms of the Creative Commons Attribution
License, Which Permits unrestricted use, distribution, and reproduction in any medium, provided the original author
and source are credited
Abstract-Face makeup is applied to cover unwanted marked on the face in order to improve a person’s
appearance. However, this is used in criminal activities since makeup can disguise the true identity of the person.
This concern serves as the basis by several studies to discover the technique and applied different methods to
optimize the detection and improve accuracy. This study aims to conduct an experiment by applying new methods
and techniques in order to provide new results which will increase the scope to consider. Furthermore, this study
utilized best performing algorithms: the Haar-Cascade classifier for face detection, Color Feature Extraction for
detection of face makeup and Local Binary Pattern Histogram algorithm for extraction and recognition of the
features which applied in the experiments considering condition from fluorescent light and sunlight, angle
variation of 0 degree, 45% upward and downward and distance of 0.5 meter and 1 meter. The study collected an
over-all of 3000 images which will serve as the training datasets. In result, the experiment marked an average
accuracy of 88.75% comprises all the methods applied. Specifically, the result showed an average result of both
sunlight and fluorescent result with no makeup marked an average score of 90% while the result with makeup
marked a score of 87.5%. Moreover, the results showed a higher recognition in near distance of 0.5 meters, the
fluorescent light recorded an accuracy result of 90% and 0% degree marked a score of 100%.
Keywords— Image processing, face recognition; makeup detection; feature extraction; color model;
I. INTRODUCTION
Image processing is widely used in object detection, visualization, sharpening, restoring of image, and in pattern
measurement that translates between the digital imaging devices and the human visual systems [1] that provides
useful information. On the other hand, different applications are being developed to recognize the face image of a
person [2]– converting the image sensor into digital images that suggests enhancement of image like extracting
the objects, changing the size, scaling, and interpreting communications across a network through compression of
an image [3].