Face recognition method based on combination of local features and global features

A technology of global features and local features, applied in character and pattern recognition, computer components, instruments, etc., can solve problems such as poor robustness and inaccurate recognition effect

Active Publication Date: 2015-01-28
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

[0004] Aiming at the technical problems existing in the above-mentioned prior art, the present invention proposes a face recognition method based on the combination of local features and global features, which overcomes the shortcomings of the prior art such as poor robustness and inaccurate recognition effect, and provides How to combine multiple methods for face recognition has been explored and researched, and some results have been achieved.

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  • Face recognition method based on combination of local features and global features
  • Face recognition method based on combination of local features and global features
  • Face recognition method based on combination of local features and global features

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Embodiment Construction

[0075] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all belong to the protection scope of the present invention.

[0076] Such as figure 1 As shown, the face recognition method of the combination of local features and global features provided by the present invention, the specific process is as follows:

[0077] The first step: the implementation of the PCA algorithm, such as figure 2 and Figure 4 shown, including:

[0078] a) Training phase

[0079] In the training phase, it is divided into the following steps:

[0080] (1) First read all the pictures in the training set into matlab sequentially thr...

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Abstract

The invention discloses a face recognition method based on the combination of local features and global features. The face recognition method comprises the steps that first, faces in an existing face database are extracted to train a training set; second, a grayscale image of an input face is extracted; third, main component features of the input face are extracted and recognized; fourth, local binary features of the input face are extracted and recognized; fifth, the main component features and the local binary features of the input face are weighted; sixth, the face matched with the input face is searched for in the existing face training set and output. The face recognition method improves the recognition rate of face recognition, combines two types of algorithms, and is wide in application prospect.

Description

technical field [0001] The present invention relates to a method for face image recognition, specifically a face recognition method based on the weighted fusion of principal component analysis (PCA) global features and local binary pattern (LBP) features. Background technique [0002] In 1888, Calton published a paper on the principle of human identification of faces in "Nature", thus proposing face recognition technology. In the following 80 years, the direction of technology development is mainly to process the gray scale and brightness of the face pictures, and then use the naked eyes to perform face recognition. So far, face recognition technology has been widely used in security, video tagging, image database retrieval, general identity verification and intelligent human-computer interaction technology. At the same time, with the advent of the Internet age, large-scale face recognition based on the Internet has become a new research topic and application direction. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/66
CPCG06V40/169G06V40/171G06V30/194
Inventor 孙锬锋蒋兴浩贾欣励李博马力天
Owner SHANGHAI JIAO TONG UNIV
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