图片库 Resources

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This implementation utilizes an image database where the detection phase begins with grayscale conversion, followed by lighting compensation and noise reduction. Edge detection is then performed, and images are normalized to ensure consistency. For feature extraction, PCA (Principal Component Analysis) is employed to extract facial features and project them into vector space. Finally, the system calculates the nearest distance between test images and reference models to determine the most matching expression category.

MATLAB 197 views Tagged