Unique Face Identification System using Machine Learning

摘要

The recognition of human faces plays an important role in many applications, for example in video surveillance and the management of facial image databases. This paper will design and implement a security system based on a machine learning algorithms. Principal Component Analysis (PCA) is the algorithm that represents the faces economically. It extracts the most dominant Eigenfaces from the present set of the faces. Comparison of video frames can be done by using this technique. Faces can be recognized in frames using the haar cascade to extract the characteristics of a human face. The SVM algorithm is used to classify between data sets using the kernel. The performance of the identification system also depends on the extraction of the attributes and their classification in order to obtain accurate results. These algorithms give different accuracy rates under different conditions, as observed experimentally. The precision and efficiency with which the model identifies people is the real added value of this paper.