Penerapan identifikasi wajah (face recognition) telah diterapkan pada komputer, laptop atau alat-alat lain yang memang dikhususkan untuk identifikasi wajah. Perkembangan smartphone khususnya android berkembang dengan cepat. Untuk menjaga keamanan supaya hanya dapat digunakan oleh pemilik telah disediakan dengan PIN, phone code, pola geser titik sentuh layar. Aplikasi identifikasi wajah digunakan sebagai pengganti PIN atau code phone pada smartphone android dibutuhkan sebagai proteksi supaya hanya pemiliknya saja yang dapat menggunakannya. Supaya proses identifikasi wajah pemilik lebih mudah perlu dilakukan konversi dari gambar true color ke grayscale proses yang digunakan adalah pointwise. Aplikasi face recognition yang dibangun membutuhkan training wajah pemilik dengan 6 pose wajah yang disimpan, kemudian akan dibandingkan dengan identifikasi wajah saat aplikasi digunakan. Hasil pengujian menunjukkan bahwa tingkat keberhasilan antara 70% - 90%. Jarak antara wajah dan kamera serta tingkat kecerahan cahaya mempengaruhi hasil dari identifikasi wajah. Tingkat keberhasilan identifikasi wajah ditentukan oleh pengambilan image, pemrosesan image, dan perhitungan dengan PCA (eigenface).Face recognition has been implemented on a computer, laptop or other device tool which is dedicated for face identification. Developments in particular android smartphones growing rapidly. To maintain the security that can only be used by owners have been provided with a PIN, phone code, pattern shear point touch screen. Face recognition application used as a substitute for or a PIN code on the phone android smartphone needed as protection so only the owner who can use it. So that the process of identification of the owner's face needs to be done easier conversion of true color images into grayscale process used is pointwise. Face recognition application that is built requires owners face training with 6 face pose saved , then will be compared with the face identification when the application is used . The test results showed that the success rate of between 70 % - 90 %. The distance between the face and the camera and the brightness of light affect the results of face identification. The success rate is determined by identifying the face image capture, image processing, and computation with PCA eigenface.
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