PERBANDINGAN ALGORITMA EIGENFACE DENGAN LOCAL BINARY PATTERN (LBP) PADA PENGENALAN WAJAH
Algorithms for image classification, in this case facial recognition, have been found, one of which is by calculating the distance between facial features such as eyes, nose, ears and lips. However, the image input used is very decisive in the recognition process, especially at the pre-processing stage, especially the feature extraction stage, because facial recognition is very dependent on the feature extraction that is carried out. Color image input in the original image used for recognition input in some studies is not optimal because the features obtained are still very complex. Therefore, in this study, the extraction method with eigenface and LBP is used which converts the original input image into a gray image and then converts it into a matrix form which will then be recognized by the Euclidean distance algorithm. The results obtained were that the algorithm of the LBP method was more optimal with 91% of faces recognized, compared to the eigenface method with 84% of faces recognized at the same size, namely 500×500 pixels
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