Abstract
Face recognition has become relevant in recent years because of its potential applications. The aim of this paper is to find out the relevant techniques which give not only better accuracy also the efficient speed. There are several techniques available for face detection which give much better accuracy but the execution speed is not efficient. In this paper, a normalized cross-correlation template matching technique is used to solve this problem. According to the proposed algorithm, first different facial parts are detected likes mouth, eyes, and nose. If any of the two facial parts are found successfully then the face can be detected. For matching the templates with the target image, the template rotates at a certain angle interval.
Highlights
Face Detection and its recognition one of the widely used technology with today's growing information technology world
In template matching two primary components are required, (I) Template Image: It is a piece of an image that we need to find in the source image
Face detection is the first state of face recognition and further detection
Summary
Face Detection and its recognition one of the widely used technology with today's growing information technology world. Template matching is a very common task of pattern recognition and a very high-level machine vision technique. It allows identifying a part of single or multiple images that matches a specific image pattern. Template matching is the best solution in pattern recognition technique, to find the best matching area for face detection. A template-based face detection technique used to identify the human face along with its different facial parts like eyes, nose, and mouth.
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