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ITS » Undergraduate Theses » T.Elektronika - PENS
Posted by wono at 19/01/2010 12:49:24  •  4296 Views

Author :
Wihandika, Randy Cahya 


Pengenalan jenis kelamin melalui wajah dapat dengan mudahdilakukan oleh manusia. Namun begitu otomatisasi dari sistem tersebut membutuhkan berbagai macam teknik. Penelitian sebelumnya menunjukkan adanya perbedaan fitur rata-rata antara wajah pria dan wanita yang dapat membedakan kedua jenis kelamin dengan tingkat akurasi yang cukup tinggi 855. Berdasarkan hasil penelitian tersebut pada proyek akhir ini diambil 10 macam variabel yang dianggap paling membedakan kedua jenis kelamin tersebut seperti tebal alis jarak mata dengan hidung lebar rahang dan lain-lain. Gambar masukan berupa gambar wajah manusia dengan rentang umur 20 hingga 25 tahun orang Indonesia dengan ekspresi netral dan dengan posisi frontal. Kemudian digunakan algoritma Jaringan Saraf Tiruan dengan menggunakan variabel-variabel tersebut pada citra sampel sebagai masukan untuk proses pelatihan.


Identification of sex through the face can easily be done by humans. However the automation of the system requires a variety of techniques. Previous research indicates the existence of the average feature differences between male and female faces that can distinguish the two sexes with accuracy 85.5. Based on the results of research in this final project taken 10 kinds of variables that are considered most distinguishes both sexes such as eyebrow thickness eyes-to-nose distance jaw width etc. Input image is an image of a human face age range 20 to 25 years people of Indonesia with a neutral expression and frontal position. Then the Neural Network algorithm is implemented using these variables in the sample image as the input of the training process. Keywords Sex Identification Face Detection Face Recognition Integral Projection Skin Color Detections Facial Feature Extraction Neural Network

KeywordsPengenal Jenis Kelamin, Deteksi Wajah, Pengenalan Wajah; Integral Projection; Deteksi Warna Kulit; Ekstraksi Fitur Wajah; Jaringan Saraf Tiruan
Subject:  Proses image
  1. Nana Ramadijanti, S.Kom, M.Kom
    Nur Rosyid Mubtada’i, S.Kom
Date Create: 12/01/2010
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Undergraduate-3100009036533
Collection ID: 3100009036533
Call Number: RSEP 006,42 Wih r

Undergraduate theses, Informatical Engineering, RSEP 006,42 Wih r, 2009

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