Facial Recognition Using Hog Algorithm and Svm Classifier

Facial recognition systems play a critical role in various security applications, including video surveillance, biometric authentication, and thermal imaging in public environments. This study presents the design and implementation of a facial recognition system utilizing machine learning techniques. The Histogram of Oriented Gradients (HOG) algorithm is employed to extract feature-rich representations by converting images into gradient distributions. To address facial alignment issues relative to the camera, Regression Trees are utilized for precise face alignment. Additionally, a Support Vector Machine (SVM) classifier is implemented to differentiate between stored identities in the database. The integration of HOG for feature extraction and SVM for classification enhances recognition accuracy, ensuring reliable facial identification.