Anti-light face recognition method based on transform domain robust watermark under big data

A robust watermarking and face recognition technology, applied in image data processing, image data processing, character and pattern recognition, etc., can solve problems such as not seeing public reports

Inactive Publication Date: 2014-08-13
HAINAN UNIVERSITY
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Problems solved by technology

At present, there are few researches on face recognition methods based on big data environment, anti-illumination and occlusion attacks, and no public reports have been seen so far.

Method used

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  • Anti-light face recognition method based on transform domain robust watermark under big data
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  • Anti-light face recognition method based on transform domain robust watermark under big data

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Embodiment Construction

[0107] Below in conjunction with accompanying drawing, the present invention is further described, simulation platform is Matlab2010a, produces 1000 groups of independent binary pseudo-random sequences (value+1 or 0), each group of sequence length is 64bit, these 1000 groups of data are corresponding 1000 numbers Watermark, W(n). Each watermark corresponds to an original image, here the 500th set of watermarks corresponds to the first image of ORL, see figure 1 , which has a size of 92x112, which is used here as the original image and the test image subjected to zero attacks.

[0108] In order to test the convenience of anti-illumination and mask attack experiments, another 1000 sets of binary random sequences (value +1, or 0), each set of sequence length is 64bit, and these 1000 sets are used as the features of 1000 original images Vector, V (n); The 500th unit is stored in the original feature vector of the first face figure in the ORL face storehouse;

[0109] The basic i...

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Abstract

The invention discloses an anti-light face recognition method based on transform domain robust watermarks under big data. The anti-light face recognition method mainly includes a watermark embedding process and a watermark extraction process, wherein face recognition is realized in the watermark extraction process. The anti-light face recognition method mainly comprises the following steps that in the watermark embedding process, firstly, global DCT is conducted on all original faces so that feature vectors can be worked out, and secondly, the watermark of each face is associated with the feature vector of the corresponding face through a hash function in cryptology; in the watermark extraction process, thirdly, the feature vector of the face to be tested is obtained, the correlation coefficient maximum value of the feature vector of the face to be tested and the original face feature vector is worked out, face recognition is completed according to a serial number corresponding to the correlation coefficient maximum value, and the corresponding embedded watermark is obtained, and fourthly, the feature vector of the face to be tested is used for watermark extraction, and the correlation coefficient of the watermark is calculated. The anti-light face recognition method has the advantages of being applicable to the big data because sampling training is not needed, and has high resistance to light, occlusion and other attacks.

Description

technical field [0001] The invention relates to the field of multimedia signal processing, in particular to a face recognition method against light attack based on transform domain robust watermark under big data. technical background [0002] As an effective biometric identification technology, face recognition technology has been paid more and more attention by industry and academia in the past 40 years. Because face recognition technology has the advantages of being highly acceptable, natural, and not easy to be detected, it has great uses in entertainment, criminal investigation, access control systems, and military affairs. [0003] At present, face recognition methods are mainly based on machine learning methods such as PCA, neural network, and SVM. Due to the need for training and learning, the recognition samples are relatively large. In the big data environment, the learning time is relatively long, and the current face Recognition methods are sensitive to illumina...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06T1/00
Inventor 李京兵李雨佳杜文才白勇
Owner HAINAN UNIVERSITY
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