Face recognition method

A face recognition and human collection technology, applied in the field of face recognition, can solve the problem that the performance of the face recognition algorithm does not reach the expected effect, and achieve the effect of accurate recognition and simple realization.

Inactive Publication Date: 2019-03-08
江苏环宇臻视智能科技有限公司
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the application of face recognition technology, due to factors such as illumination, occlusion, scale or movement of the face area, the performance of the face recognition algorithm cannot reach the expected effect

Method used

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Embodiment Construction

[0022] In order to deepen the understanding of the present invention, the present invention will be further described below in conjunction with examples, which are only used to explain the present invention and do not constitute a limitation to the protection scope of the present invention.

[0023] A method for face recognition, the steps are as follows:

[0024] 1) Lengthen each face image in the training set by one column as a vector;

[0025] 2) Add up all the faces in the corresponding dimensions, calculate the average, and get an "average face";

[0026] 3) Subtract the average face image from each image to obtain the data matrix of the difference image;

[0027] 4) Calculate the covariance matrix, and then perform eigenvalue decomposition on it to obtain the desired eigenvector (eigenface);

[0028] 5) Project the images of the training set and the test set onto these feature vectors, and then find the nearest neighbor in the training set for each image of the test se...

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Abstract

The invention relates to a face recognition method, which comprises the following steps of 1) elongating each human face image of a training set by one column as a vector; 2) adding up all the faces on the corresponding dimensions and then averaging them to obtain an average face; 3) subtracting that average face image from each image to obtain a data matrix of the difference image; 4) calculatingthat covariance matrix, and then decomposing the covariance matrix into eigenvalue, and obtaining a desired eigenvector (eigenface); 5) projecting that images of the train set and the test set onto these eigenvectors, and then finding the nearest neighbor of the training set for classification and recognition for each image of the test set. The method has the characteristics of accurate recognition, simple realization, safety and practicability.

Description

technical field [0001] The invention relates to the field of face recognition, in particular to a face recognition method. Background technique [0002] With the rapid growth of application requirements in security access control and financial trade, biometric identification technology has received new attention. Currently, new advances in microelectronics and vision systems have reduced the cost of realizing high-performance automatic identification technology in this field to an acceptable level. Face recognition is one of the most widely used technologies in all biometric methods. Face recognition technology is a new technology that has risen in recent years but is not well known. People often see the miraculous application of this technology in movies: the police will enter the photos of the suspect's face that they secretly photographed into the computer, compare them with the information in the police database, and find out the details of the suspect. information and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/172G06F18/2413
Inventor 朱彬高飞赵文豪潘景树
Owner 江苏环宇臻视智能科技有限公司
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