Face detection and recognition can be applied to numerous fields, and it is primarily used for improving security. For security purposes, facial recognition is considered to be the most reliable and accurate technology for identifying a person. Improvements in security systems can be made through this technology without causing any inconvenience. This article discusses several systems, such as smart home security systems, autonomous face detection systems, automotive security-based systems, face detection for surveillance applications, and multi-face recognition systems. Various detection mechanisms include such as Local Binary Pattern Histogram (LBPH), Support Vector Machine (SVM), AdaBoost learning algorithm, Haar Classifier Algorithm, and Principal component Analysis (PCA). A detailed study is carried out with these advanced techniques and their advantages, disadvantages and accuracies are compared and contrasted. According to the investigations, the Haar classifier appears to be superior to other techniques due to its accuracy and features.