Sparse-regularization-based face recognition method capable of realizing multiband face image information fusion

A face image information and face recognition technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems that changes in expressions and postures cannot be well adapted, single fused features, high feature dimension, etc. question

Inactive Publication Date: 2013-08-28
SHANGHAI JIAO TONG UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

The features fused by this type of fusion method are generally relatively single, and the feature dimension is relatively high.
[0004] Although multi-band images other than visible light have good robustness to changes in illumination intensity, there are stil

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  • Sparse-regularization-based face recognition method capable of realizing multiband face image information fusion
  • Sparse-regularization-based face recognition method capable of realizing multiband face image information fusion
  • Sparse-regularization-based face recognition method capable of realizing multiband face image information fusion

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Embodiment 1

[0028] Such as figure 1 Shown: this embodiment comprises the following steps:

[0029] Step 1: Collect visible, near-infrared, mid-infrared, far-infrared, and thermal-infrared training images

[0030] The collection refers to: the collected visible light, near-infrared, mid-infrared, far-infrared and thermal infrared face images need to be frontal face images, and in order to ensure the diversity of training images, images need to be collected under different conditions, Such as under different lighting and facial expression changes.

[0031] Step 2: Image normalization, background removal, and illumination preprocessing, specifically: normalize the face image through measures such as human eye positioning, and then cover the mask to remove the background; further, in order to remove the illumination To avoid the influence of uniformity, add Gamma correction or retina filter and other light preprocessing methods.

[0032] The human eye positioning is realized by using the A...

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Abstract

The invention relates to a sparse-regularization-based face recognition method capable of realizing multiband face image information fusion and belongs to the technical field of image processing. The method comprises the following steps of: 1, acquiring visible-light, near-infrared, intermediate-infrared, far-infrared and thermal-infrared training images; 2, performing normalization, background removal and illumination preprocessing; 3, extracting visible-light, near-infrared, intermediate-infrared, far-infrared and thermal-infrared sample facial features; 4, selecting the sample facial features based on a sparse regularization method, evaluating coefficient and endowing weight under the classification significance according to the sample facial features, and fusing the sample facial features to obtain feature vectors representing the samples to serve as index vectors; 5, forming a feature set according to the index vector; 6, segmenting a facial part from an image to be tested, performing operation of the step 2 to step 4 on the facial part to be tested to obtain a feature vector of the facial part to be tested; and 7, sequentially calculating the distance between the feature vector of the facial part to be tested and the feature vectors of the feature set, and selecting the sample which corresponds to the feature set with the minimal distance and is the person of the image to be tested. The method has the advantages that change of accessories, shelter and the like is overcome; the recognition precision is high; and the application range is wide.

Description

technical field [0001] The present invention relates to a method in the technical field of image processing, in particular to a face recognition method that combines visible light, near-infrared, mid-infrared, far-infrared and thermal-infrared face information through a sparse regularization algorithm. Background technique [0002] Face recognition technology uses a computer to obtain face images and perform analysis and preprocessing, then extracts features that can effectively represent face images in a specific way, and finally uses machine learning to identify face images. Face recognition is widely used in human-computer interaction systems, security verification systems, verification of driver's licenses and passports, and identification of criminals. With the development of information and network technology in recent years, face recognition has become one of the most concerned issues in the field of pattern recognition. [0003] One of the most important research to...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 王亚南苏剑波赵玥曾明
Owner SHANGHAI JIAO TONG UNIV
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