Experimental research on identification of face in a multifaceted condition with enhanced genetic and ant colony optimization algorithm

Abstract

Digital images have a substantial information and characteristics quantities But until today, a complete efficient mechanism to extract these characteristics in an automatic way is yet unknown Referring to facial images its detection in an image is a setback that requires a meticulous investigation due to its high complexity Face identification is a crucial application of visual object detection and it is one of the main components of face analysis and understanding with face localization and face recognition It becomes a more and more complete domain used in a large number of applications among which we find security new communication interfaces biometrics and many others Here the aspects of genetic in face recognition is investigated Genetic Algorithms are characterized as one search technique inspired by Darwin Evolutionist Theory shaped using some selection mechanisms used in nature according with that individuals who are fit in a population are those who have more survival possibility when adapting themselves more easily to the changes that occur in their habitats Genetic Algorithm is efficient in reducing computation time for a huge heap space Face identification from a very huge heap space is a time consuming task hence genetic algorithm based approach is used to recognize the unidentified image within a short span of time