FACIAL FEATURE INDENTIFICATION AND COMPARISION UISNG KNN ALGORITHM
DOI:
https://doi.org/10.61841/bbw8s789Keywords:
Face recognition, face identification, local binary pattern (LBP), k-nearest neighbor (K-NN)Abstract
Biometrics is the statistical analysis of the user’s unique physical and behavioral characteristics. This technology is used for identification and access control, or else for identifying the individuals who are under surveillance. Some examples include palm veins, face recognition, hand geometry, iris recognition, retina, etc., physiological traits or behavioral characteristics. They are the way to measure the physical characters to verify their identity. Once measured, the information is compared and matched in the database. Features extracted from the facial images play a major role in the security system. This research paper explains how facial features are identified using the KNN algorithm. Finally, the proposed method is compared with existing methods. The comparison table represents that DLBP and RLBP with KNN classifiers provide better results in terms of accuracy than existing methods.
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