scholarly journals Klasifikasi Usia Berdasarkan Citra Wajah Menggunakan Algoritma Artificial Neural Network dan Gabor Filter

2020 ◽  
Vol 2 (2) ◽  
pp. 60-67
Author(s):  
Sudirman Melangi

Pengklasifikasian kelompok usia dibangun berdasarkan ciri-ciri dari fitur wajah. klasifikasi usia berdasarkan citra wajah perlu dilakukan dengan lebih akurat agar dapat berguna dalam sistem pengenalan usia manusia. Beberapa kesulitan dalam pengenalan wajah yang sering muncul karena variabilitas wajah seperti ekspresi, penuaan, variasi kumis dan sebagainya. Metode filter gabor dikenal sebagai detektor ciri yang sukses serta memiliki kemampuan mengeliminasi parameter variabilitas wajah yang pada metode lainnya sering menggangggu dalam proses pengenalan. Dengan menggunakan metode Gabor filter yang terbukti handal digunakan untuk memecahkan masalah agar pengenalan usia berdasarkan wajah dapat dilakukan dengan lebih akurat. Hasil penelitian menunjukkan bahwa penerapan metode Gabor Filter dan Artificial Neural Network pada masalah pengenalan usia berdasarkan citra wajah berhasil mendapatkan akurasi yaitu sebesar 83% dengan menggunakan pengujian Confusion Matrix. Dengan demikian penerapan metode Gabor Filter dan Artificial Neural Network pada masalah pengenalan usia berdasarkan citra wajah cukup akurat, dan dapat diimplementasikan. Kata kunci: Klasifikasi Usia, Wajah, ANN, Gabor Filter. Classification of age groups is built on the characteristics of facial features. Age classifications based on facial images need to be done more accurately in order to be useful in the human age recognition system. Some difficulties in facial recognition that often arise due to facial variability such as expression, aging, mustache variations and so on. Gabor filter method is known as a successful feature detector and has the ability to eliminate facial variability parameters which in other methods often interfere in the recognition process. By using the Gabor filter method which is proven to be reliable it is used to solve problems so that face recognition based on faces can be done more accurately. The results showed that the application of the Gabor Filter and Artificial Neural Network method on the problem of age recognition based on face images managed to get an accuracy of 83% using the Confusion Matrix test. Thus the application of the Gabor Filter and Artificial Neural Network method to the problem of age recognition based on face images is quite accurate, and can be implemented.Keywords: Age Classification, Face, ANN, Gabor Filter

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