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Integration of PCA and Euclidean Distance Methods for Human Face Recognition Image Processing

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This method achieves 95% accuracy in face recognition, utilizing PCA and Euclidean Distance for classification.

The integration of PCA and Euclidean Distance resulted in a 95% accuracy in face recognition.
Feature extraction using PCA reduced facial features effectively from a matrix size of 34 × 20400 to 34 × 200.
The initial image processing involved converting RGB images to the YCbCr colour model and applying pixel segmentation.
Labeling and cropping were performed after detecting faces, followed by noise removal using morphological opening.

Indriyono et al. (2025) studied this question.

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