Facial Feature Extraction and Principal Component Analysis for Face Detection in Color Images

摘要: A hybrid technique based on facial feature extraction and Principal Component Analysis (PCA) is presented for frontal face detection in color images. Facial features such as eyes mouth are automatically detected properties of the associated image regions, which extracted by RSST segmentation. While points identified using redness property a simple search strategy relative to position carried out identify eye from set regions. Priority given regions signal high intensity variance, thereby allowing most probable be selected. On detecting two eyes, verification step Eigenface theory applied normalized space distance between points.