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Regional feature extraction face recognition method

A feature extraction and face recognition technology, applied in the field of face recognition, can solve the problem of low face recognition rate

Active Publication Date: 2020-02-21
XI'AN POLYTECHNIC UNIVERSITY
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Problems solved by technology

[0007] The purpose of the present invention is to provide a face recognition method for subregional feature extraction, which solves the problem of face recognition caused by the influence of non-limited environment in the prior art. low rate problem

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  • Regional feature extraction face recognition method

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Embodiment Construction

[0078] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0079] The present invention a kind of regional feature extraction face recognition method, its process is as follows figure 1 As shown, the specific steps are as follows:

[0080] Step 1, obtain the face image to be recognized;

[0081] Step 2, preprocessing the face image obtained in step 1 using a multi-task convolutional neural network, performing face detection, and marking the key points of the face;

[0082] Among them, the multi-task convolutional neural network (MTCNN) mainly includes three sub-networks: P-Net, R-Net, O-Net; P-Net is a fully convolutional network, used to generate candidate boxes and frame regression vectors, and use Border regression vector and non-maximum value suppression method to screen these candidate boxes; send the filtered results to R-Net, and continue to use the frame regression vector and non-maximum va...

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Abstract

The invention discloses a regional feature extraction face recognition method. The method is specifically implemented according to the following steps: 1, obtaining a to-be-recognized face image; 2, preprocessing the acquired face image by using a multi-task convolutional neural network, and marking key points of the face; 3, according to different key point position information, segmenting the human face into an expression variable region and an expression invariable region; 4, inputting the images of the expression variable region and the expression invariable region into a Gabor & block LBPfeature extraction channel to obtain a feature histogram containing face feature information; and 5, processing the feature histogram containing the human face feature information in the step 4 by using a linear discrimination method, and matching the processed human face feature information with human face features in a database to obtain a human face recognition result. According to the regional feature extraction face recognition method, the problem that the face recognition rate is low due to the influence of a non-limited environment in the prior art is solved.

Description

technical field [0001] The invention belongs to the technical field of face recognition methods, and relates to a face recognition method for subregional feature extraction. Background technique [0002] Face recognition technology is an important part of machine vision. Because of its convenience, ease of implementation, and non-invasiveness, it has been widely used in all aspects of daily life such as video surveillance, access control systems, and station security checks. [0003] In recent years, with the continuous innovation of face recognition technology, people have higher and higher requirements for recognition accuracy. Since the accuracy of the traditional face recognition system is tested in a limited environment, satisfactory results can be achieved. However, in an unrestricted environment, since the input face image is affected by factors such as illumination, noise, and facial expression changes, the accuracy of face recognition will be greatly reduced. [...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/174G06V40/168G06V40/172
Inventor 李云红聂梦瑄周小计穆兴李传真刘旭东
Owner XI'AN POLYTECHNIC UNIVERSITY
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