Revolutionizing Facial Feature Extraction with AI: An Innovative Approach

This paper provides a technique for detecting human faces & extracting their features based on segmentation of skin tone & facial structure. The system goes through several stages. The method first searches for regions where faces might be present by segmenting skin tone. After performing various morphological operations on skin, it uses aspect ratio of a face to find viable face blocks. face blocks are then used to extract additional features. Therefore, one may identify and validate a person's image using their face features by using this biometric attribute. To enhance facial recognition, numerous researchers have employed Support Vector Machine (SVM), Principal Component Analysis (PCA), a combination of SVM and PCA, PCA with an Artificial Neural Network, and even the conventional PCA-SVM. Due to PCA-ANN's limited dataset limitation, PCA-SVM is superior to PCA-ANN. To extract features, relative location & size are used. If algorithm is unable to identify even one feature in a prospective face block, it rejects face block.