Detection and Recognition of Face Using Deep Learning

Face detection applications using digital photos are critical in the face recognition process. This application is used in biometric recognition systems, search systems, and security systems. Artificial intelligence and machine learning are combined in computer vision. Using computer techniques, it can extract information from images and videos. Many prior studies used various methods and programming languages to create face detection applications. The most crucial aspect of computer vision is object detection. Locating the face is the primary step in computer vision to detect the face part in the input image. For the Java programming language, the Open-Source Computer Vision Library (OpenCV) is a free open-source library for object detection. The Haar cascade classifier is one of the object detection techniques. By counting the number of pictures in a square form on an image, this technique can easily convert an object. The use of face detection in digital photos using the Haar Cascade Classifier and image transformation into grey / grayscale images using the OpenCV library are discussed in this paper. This methodology provides the better investigation accuracy of the outcomes in input photos.