Creating an advanced Face Detection and Recognition algorithm for Enhanced Information security - Bhoyar, Dinesh; Ninave, Diksha; Zode, Pravin; Arvind R. Bhagat Patil; Karale, Shivkumar; Khobragade, Rajesh (International Journal of Intelligent Systems and Applications in Engineering, 2023)
Face is crucial in our social interactions, serving as the initial focal point for recognition and emotional interpretation. Due to its non-invasive nature, precision, and speedy outcomes, the use of Live Face Recognition has gained a significant amount of attention in security systems. The process of recognizing human faces in real time consists of two steps: Face detection and Face recognition. The reason behind our utilization of Viola-Jones algorithm in face detected is due to its exceptional accuracy and efficient real-time processing capabilities. Additionally, this algorithm is available in Open-CV and can be implemented using Python. When considering Face recognition, there are two key stages to keep in mind - the training phase, the evaluation phase. During the schooling phase, the algorithm is instructed using image sample that needs to be learned. On the other hand, during the estimation phase and the test image is matched against all the previously trained samples in this dataset. Local Binary Patterns Histogram is utilized to extract the facial functions from the detected faces in a stay stream. We can achieve face recognition by utilizing the LBPH method.