Face recognition method based on PCA (principal component analysis) image reconstruction and LDA (linear discriminant analysis)

Abstract

The invention discloses a face recognition method based on PCA image reconstruction and LDA and belongs to the technical field of computer image processing and pattern recognition. The face recognition method is based on a principal component analysis algorithm; an intra-class covariance matrix serves as a generation matrix for acquiring face feature subspaces of individuals; then an image to be recognized maps the feature subspaces to extract features; the image is reconstructed according to feature values; a residual image is subjected to the linear discriminant analysis; and finally, face recognition is realized by a minimum distance classification recognition algorithm. Compared with the prior feature subspace method, the face recognition method can better extract the face features of different people, and the face recognition rate is increased effectively. In addition, when a face database is required to be expanded, only the newly added faces are required for feature face training; not all the face feature subspaces are retrained; and the face recognition method also has good extendibility.

Description

technical field [0001] The invention relates to a face recognition method based on PCA image reconstruction and LDA, belonging to the technical field of computer image processing and pattern recognition. Background technique [0002] Face recognition technology is a technology that uses computers to analyze face images, extract effective identification information from them, and identify personal identities. For the input face image, first judge whether there is a face in it, and if there is a face, then further Given the position, size and location information of each major facial organ of each face, and based on these information, further extract the identity features contained in each face, and compare them with the faces in the known face database, Thereby identifying the identity of each face. Face recognition technology involves the knowledge of pattern recognition, image processing, computer vision, physiology, cognition and many other disciplines, and is closely rel...

AI Technical Summary

Problems solved by technology

[0006] Due to the above advantages of face recognition technology, face recognition technology is widely used in many fields, such as the field of judicial departments, where the public security department can quickly retrieve the face information in the file system through the photos or facial features of criminal suspects. Comparing photos can improve the efficiency of criminal investigation and solving cases; in the field of public security, it is very difficult to find specific targets in densely populated places such as stations, airports, hotels, etc. In the field of access control system, the identification technology of traditional access control system has risks such as forgery and false use, and the face recognition system is a kind of biometric identification. These risks do not exist, and it will bring more convenience to users; in the field of information security, such as cardholder identity verification of various bank cards and financial cards, and with the development of network informatization, electronic banking is used more and more frequently, but the current security mechanism of electronic banking mainly relies on account numbers, passwords, digital certificates, etc. These information are easy to be copied and disseminated. Face recognition technology is a more secure and reliable identity authentication technology. Therefore, it is very useful in information security and civil fields

[0007] Although humans can identify a person from a face without difficulty, there are still many difficulties in using a computer to perform fully automatic face recognition, which is manifested in: the face is a kind of natural structural target with quite complex detail changes, appearance , expression, skin color, etc.; face changes with age; hairstyle, glasses, beard and other decorations block the face; the image formed by the face is affected by illumination, imaging angle, imaging distance, etc.

Images