The Development of a Real-Time Facial Recognition System Using the Haar-like Feature-Based Detection Technique
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The objective of this research is to Development of a Real-Time Facial Recognition System Using the Haar-like Feature-Based Detection Technique. A model is developed where the system recognizes faces as one of the methods for verifying and confirming the identity of individuals, utilizing unique spatial features of the face. It extracts the spatial and differential features of the face from photographs, digital images, or video footage for processing. By transforming them into a template, the system compares them with a facial database to find individuals with the closest resemblance to the input image. The system then presents the identified face as the output. The development process involves data collection, facial detection, and feature extraction through training, such as eyes, eyebrows, and mouth, among others. The model development and testing consist of a dataset of 100 facial images and 100 non-facial images. The experiment on facial detection yielded a 91.00% accuracy rate, while the application of the model on test faces resulted in a 78.00% accuracy rate.
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