Ivransa Zuhdi Pane
Universitas Multimedia Nusantara

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The Effect of Using Histogram Equalization and Discrete Cosine Transform on Facial Keypoint Detection Adhi Kusnadi; Lionissa Ratnawati Darmawan; Ivransa Zuhdi Pane; Syarief Gerald Prasetya
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 2: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2032

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.
Image Restoration Effect on DCT High Frequency Removal and Wiener Algorithm for Detecting Facial Key Points Adhi Kusnadi; Vincent Anderson Ngadiman; Ivransa Zuhdi Pane; Syarief Gerald Prasetya
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 2: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2033

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.
Pengembangan Aplikasi Manajemen Informasi Magang Terowongan Angin Kecepatan Rendah Indonesia Ivransa Zuhdi Pane
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 4, No 3 (2020)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (748.367 KB) | DOI: 10.30998/string.v4i3.5915

Abstract

An internship information management application at Indonesian Low Speed Wind Tunnel facility is useful for supporting managerial tasks related to internship activities, ranging from registration, task allocation, task implementation supervision to evaluation of the work results of the apprentices. This application is expected to not only support productivity and performance, but also provide input for management in making decisions related to the employment of apprentices in order to realize a synergy that has a positive impact on the smooth process of the wind tunnel test service business as a whole. To realize it, a software engineering activity by adopting prototyping methodology is carried out to build the application to be then operated in a desktop platform and be used as needed