FACE IMAGE RETRIEVAL SYSTEM USING COMBINATION METHOD OF SELF ORGANIZING MAP AND NORMALIZED CROSS CORRELATION

Amir Saleh (Universitas Prima Indonesia)
Diky Suryandy (Universitas Prima Indonesia)
Jesron Nainggolan (Universitas Prima Indonesia)

INFOKUM
Vol. 9 No. 2, June (2021): Data Mining, Image Processing and artificial intelligence

Content based image retrieval (CBIR) is one method in computer vision that is widely applied in various fields of life. In this study, two algorithms will be combined, namely self organizing map (SOM) and normalized cross correlation (NCC) to test the method in the face image retrieval system. The SOM algorithm is used to perform learning on the system created and the NCC method is used to calculate the proximity value between the input image and the image contained in the database to be displayed as the result of image retrieval. The test results in the proposed research show good results with an accuracy rate of face image retrieval of 93.62%. This percentage is higher than using the usual SOM method with an accuracy rate of face image retrieval of 91.62%.