Wulandari, Meirista Real time face detection using haar-like feature method and local binary pattern method. IOP Conference Series: Materials Science and Engineering.
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Junaidy_2019_IOP_Conf._Ser. _Mater._Sci._Eng._508_012076.pdf Download (568kB) |
Abstract
Face detection is one of the important roles in face identification. There are some difficulty factors in the process. Therefore, some methods are developed. This study aims to compare Haar-Like Feature method and Local Binary Pattern (LBP) method for face detection. Samples are 25 people in the Electric Engineering Department. Based on the result, Haar-Like Feature method is more accurate than LBP method. Haar-Like method can detect 20 faces from 25 faces with success rate of 80% while LBP can detect 14 faces from 25 faces with success rate of 56%. From this research, it is taken that both methods are having in trouble detecting face from someone that use glasses, have dark skin, or having facial hair.
| Item Type: | Article |
|---|---|
| Subjects: | Artikel |
| Divisions: | Fakultas Teknik > Teknik Elektro |
| Depositing User: | Puskom untar untar |
| Date Deposited: | 12 Apr 2023 03:59 |
| Last Modified: | 12 Apr 2023 03:59 |
| URI: | http://repository.untar.ac.id/id/eprint/39385 |
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