Perbandingan Metode Deteksi Wajah Menggunakan OpenCV Haar Cascade, OpenCV Single Shot Multibox Detector (SSD) dan DLib CNN

  • Lia Farokhah STMIK Asia Malang
DOI: https://doi.org/10.29207/resti.v5i3.3125
Keywords: Face detection, Open CV, Dlib, Performance comparison

Abstract

Comparison of methods in face detection is needed to provide recommendation of best method. This study compared three methods in face detection, namely OpenCV haar cascade, OpenCV Single Shot Multibox Detector (SSD) and Dlib CNN. Face detection is focused on five challenging conditions, namely face detection in head position obstacles, wearing face masks, lighting, background images that have a lot of noise, differences in expression. Data testing is taken randomly on google with reference to one image consisting of more than one detected face with wild condition. The results of the comparative analysis in wild condition show that the OpenCV haar cascade has more weaknesses with a performance percentage of 20% compared OpenCV SSD and Dlib CNN method. Performance results of SSD and Dlib CNN have the same performance in the five conditions tested, which is about 80%.

 

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Published
2021-06-29
How to Cite
Lia Farokhah. (2021). Perbandingan Metode Deteksi Wajah Menggunakan OpenCV Haar Cascade, OpenCV Single Shot Multibox Detector (SSD) dan DLib CNN . Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(3), 609 - 614. https://doi.org/10.29207/resti.v5i3.3125
Issue
Vol 5 No 3 (2021): Juni 2021
Section
Information Technology Articles

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