Jurnal SINTA 2
Cara Cepat Untuk Mendeteksi Keberadaan Wajah Pada Citra Yang Mempunyai Background Kompleks Menggunakan Model Warna YCbCr dan HSV
Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK) · Vol. 2 No. 2 (2015) · pp. 138–142
- ISSN
- 2528-6579, 2355-7699
- Published
- 2015-07-22
- Publisher
- Fakultas Ilmu Komputer, Universitas Brawijaya
- Language
- en
Abstract
AbstrakPendeteksi wajah dari sebuah citra baik berupa gambar diam maupun bergerak merupakan topik penting dan menarik saat ini. Proses deteksi keberadaan wajah ini menjadi dasar dari proses pengenalan wajah yang mempunyai banyak implementasi baik pada bidang keamanan maupun sosial media. Tujuan dari proses deteksi wajah adalah untuk mengetahui apakah ada wajah dari suatu citra, kemudian menemukan letak keberadaan wajah. Pendeteksian wajah adalah tahapan penting dari aplikasi yang memanfaatkan keberadaan wajah pada suatu citra. Implementasinya cukup banyak terutama di bidang biometri keamanan dan sosial media. Riset ini mengusulkan deteksi wajah menggunakan 3 tahapan umum yaitu segmentasi warna kulit manusia, binarisasi dan penentuan region garis serta deteksi wajah menggunakan ruang warna YCbCr dan HSV. Dalam penelitian ini dilakukan deteksi wajah pada 10 citra yang memiliki background yang kompleks. Pendeksian lokasi wajah didasarkan pada temuan hole mata yang simetris. Wajah yang terlalu kecil membuat keberadaan mata hanya terdeteksi sebelah sehingga mengakibatkan wajah tidak terdeteksi. Hasil evaluasi didapatkan tingkat akurasi rata-rata deteksi wajah mencapai 83,4% dengan kecepatan rata-rata 6530 piksel/detik.Kata kunci: Deteksi Wajah, Biometri, Segmentasi, YCbCr, HSV, Region GarisAbstractFace detection of an image either still or moving image is an important and interesting topic today. Face detection process where it became the basis of face recognition process that has many implementations, both in the field of security and social media. The aim of the face detection process is to determine whether there is a face from an image, and then locate the whereabouts of the face. Face detection of an image, either a statis or moving image Face detection is an important phase in application system to utilize face location in an image. It is so many implementations such asspecially for security and sociality biometrics field. Here, it suggest to detect the face location with 3 steps, skin human color segmentation step, binnerization step, and locate line region then detection step of face location by YCbCr and HSV color region. Here, ten images which have a complex background are implemented. To detect face location based on finding symetris of eyes hole. The faces which are too small made the eyes locations are only detected a half, so the face can’t detect. The evaluation result obtained average of accuration of face detection 83,4% with average time to detect 6530 pixel/second.Keywords: Face detection, Biometry, Segmentation, YCbCr, HSV, Line Region
Collaboration network of the authors
13 authors · 25 co-authorship links
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- University of Brawijaya
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Imam Cholissodin | University of Brawijaya | 2 |
| Putra Pandu Adikara | University of Brawijaya | 1 |
| Edy Santosa | University of Brawijaya | 1 |
| Candra Dewi | University of Brawijaya | 1 |
| Sutrisno . | Affiliation unknown | 1 |
| Rina Christanti | University of Brawijaya | 1 |
| Arief Andy Soebroto | University of Brawijaya | 1 |
| Randy Cahya Wihandika | University of Brawijaya | 1 |
| Dewi Novita Sari | University of Brawijaya | 1 |
| Indriati . | Affiliation unknown | 1 |
| Matyus Garbela Ismanto | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.