The Application Of Genetic Algorithms In Face Recognition

As a focus and difficulty in the pattern recognition and image processingfields, face recognition (FR) research has an important significance, eitherfor its widely practical application. Human faces have large variation inshape at different time. Many influences, such as lighting, background,facial expressions and facial details, will easily affect the recognizeresult. This paper introduces the commonly used face recognition. Segmenting theface, we built the methods of the face and mathematical model. The applicationof genetic algorithms in face recognition technology to give a demonstration.In the genetic algorithms,we design chromosome by a binary chain comprised by 2genes. Selection operator is designed to be 'elite selection'. Crossover operators usinghybrid chromosome elements mixed together with the chromosome from the mother tochoose the best individual principles.In order to avoid early in the mutation operator isusing the logical operations generated by the two chromosomes. So that the same gene willnot have all 1 or all 0.In addition, the proportion of this plan in accordance with standardfeatures Face to Face, features a set of specific measurement featured deviation anddevelops a left eye, right eye, nose and mouth area of evaluation function.Thus, the geneticalgorithm to adapt to function.This paper is divided into three parts.The first part of the significance of facerecognition, face recognition systems development background and the main content.Thesecond part details of the main methods of static image recognition. Then the geneticalgorithms and genetic algorithms in image processing applications.The third partintroduces the related analysis of face recognition system simulation thatI used. The originally of the text identified the analysis and prospectsof face recognition and genetic algorithms.