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Face feature identification method and system based on frequency domain division

A face feature and recognition method technology, applied in the field of face recognition, can solve the problems of being unable to cope with complex noise situations, loss of image detail information, and affecting recognition results, etc., to achieve fast face recognition, good anti-noise ability, Robust Effect

Active Publication Date: 2017-10-24
北京飞搜科技有限公司
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AI Technical Summary

Problems solved by technology

[0005] Disadvantages: This method can only perform data enhancement on known interference, and cannot deal with complex noise situations in reality
[0007] Disadvantages: Image reconstruction may lose some image detail information to a certain extent, affecting the recognition effect
At the same time, the operation of rebuilding is time-consuming

Method used

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  • Face feature identification method and system based on frequency domain division
  • Face feature identification method and system based on frequency domain division
  • Face feature identification method and system based on frequency domain division

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Embodiment Construction

[0026] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0027] Such as figure 1 As shown, the present invention provides a kind of facial feature recognition method of frequency domain division, comprising:

[0028] S101. Perform FFT transformation on the training image X to obtain the frequency distribution F=FFT(X). Specifically, the storage of the image X in the computer is a three-dimensional array, which is respectively channel (channel), height (height), width (width) ); wherein the image in the RGB format has 3 channels, respectively corresponding to Red, Green, and Blue, and fast Fourier transform is carried out for each channel, i.e. FFT transform, because the FFT change is a technology known in the art, here will not repeat;

[0029] S102. Divide the frequency dist...

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Abstract

The invention discloses a face feature identification method and system based on frequency domain division. The face feature identification method comprises carrying out FFT transformation on a training image to obtain frequency distribution; dividing the frequency distribution to obtain a plurality of frequency components; carrying out IFFT transformation on each frequency component to obtain image components corresponding to different frequency components; combining with a tag of the training image to obtain processed training data; training a convolutional neural network by means of the processed training data to obtain a network parameter; processing an input image to be identified through a model to obtain a feature of the image to be identified; carrying out sample comparison of the image to be identified by calculating the Euclidean distance of the feature to obtain a face feature, and completing face identification. The face feature identification method based on frequency domain division is fast in face identification speed, high in accuracy, strong in robustness and good in noise resisting ability.

Description

technical field [0001] The invention relates to the field of face recognition, in particular to a face feature recognition method and system based on frequency domain division. Background technique [0002] Existing face recognition systems generally preprocess face images, use convolutional neural networks for training, and obtain the weights of the trained networks to complete the training. In the application, the picture of the face is used as input, and the feature representation of the face is obtained through the trained convolutional neural network, and then the recognition of the face is realized by comparing the features. Most of the training images come from the Internet, which are relatively high-quality images. There are many low-quality images in the actual images, such as low resolution, blur, noise, etc., and the network cannot extract appropriate features, which reduces the recognition effect. [0003] The existing image preprocessing techniques are as foll...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/168
Inventor 赵钰董远白洪亮
Owner 北京飞搜科技有限公司
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