Kusnadi, Adhi and Ngadiman, Vincent Anderson and Pane, Ivransa Zuhdi and Prasetya, Syarief Gerald (2020) Image Restoration Effect on DCT High Frequency Removal and Wiener Algorithm for Detecting Facial Key Points. EECSI (Electrical Engineering Computer Science and Informatics). ISSN 2407-439X
Full text not available from this repository.Abstract
This study aims to figure out the effect of using Histogram Equalization and Discrete Cosine Transform (DCT) in detecting facial keypoints, which can be applied for 3D facial reconstruction in face recognition. Four combinations of methods comprising of Histogram Equalization, removing low-frequency coefficients using Discrete Cosine Transform (DCT) and using five feature detectors, namely: SURF, Minimum Eigenvalue, Harris-Stephens, FAST, and BRISK were used for test. Data that were used for test were obtained from Head Pose Image and ORL Databases. The result from the test were evaluated using F-score. The highest F-score for Head Pose Image Dataset is 0.140 and achieved through the combination of DCT & Histogram Equalization with feature detector SURF. The highest F-score for ORL Database is 0.33 and achieved through the combination of DCT & Histogram Equalization with feature detector BRISK.
| Item Type: | Article |
|---|---|
| Subjects: | 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 004 Computer Science, Data Processing, Hardware |
| Divisions: | Faculty of Engineering & Informatics > Informatics |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 11 Oct 2021 09:21 |
| Last Modified: | 11 Oct 2021 12:00 |
| URI: | https://kc.umn.ac.id/id/eprint/18633 |
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