Ethnic Characterization in Amalgamated People for Airport Security Using a Repository of Images and Pigeon-Inspired Optimization (PIO) Algorithm for the Improvement of Their Results

Abstract

Nowadays, the latent danger that there is a terrorist attack in an airport anywhere in the world is a matter of first importance, that is why biometrics plays a vital role in our daily life—In our case it can determine the Facial characteristics of an individual, including their ethnicity. Given that this type of intelligent applications that detect and determine the facial attributes of people is highly safe and convenient, our society makes use of this technology almost everywhere, from the surveillance in the airport, as has been mentioned, to smart homes. in general in any aspect related to a smart city. In comparison with other biometric solutions, facial recognition produces greater advantages, since it does not require interaction or the permission of the subject. From this point of view, it represents a fast and effective way to increase our level of security, especially in open and crowded places. Automated facial recognition is a modern concept, and novel research related to image analysis. It was born in the 1960s and is still in permanent development. In 2006, the project “Facial Recognition Grand Challenge” (FRGC) evaluated the facial recognition algorithms available at that time. Tests with 3D scanners, high-quality images, and iris photographs. The FRGC showed that the algorithms available at that time were 10 times more accurate than those of 2002 and 100 better than those of 1995. Some recognition methods were able to overcome humans in face recognition and could even distinguish between twins identical In our case and using a novel algorithm called Pigeon-Inspired Optimization (PIO) Algorithm.