Composite gradient vector-based face recognition method

A gradient vector, face recognition technology, applied in the field of face recognition based on compound gradient vector, can solve the problem of lack of synchronous adjustment of face recognition methods

Inactive Publication Date: 2012-01-18
LIAONING TECHNICAL UNIVERSITY
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Problems solved by technology

[0004] Compared with the recognition systems in the biological world, a general weakness of

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  • Composite gradient vector-based face recognition method
  • Composite gradient vector-based face recognition method
  • Composite gradient vector-based face recognition method

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Embodiment Construction

[0046] The present invention will be described in detail below in conjunction with the examples.

[0047] The following takes the CMU-PIE face database as an example to illustrate the implementation process of this method. The face database contains 41,368 facial images of 68 testers with different postures, different lighting and different expressions. The changes in posture and lighting are collected under strictly controlled conditions through multi-angle transformation. Samples, each with four different sets of expression, lighting, light and pose. The implementation process is as follows:

[0048] 1. Feature extraction stage

[0049] First, the face images of the four sets are normalized to obtain the target area of ​​each face image respectively.

[0050] Then, calculate the distribution probabilities and information entropy values ​​of pixels corresponding to each gray scale in the target area of ​​each face image, and count the extreme points of information entr...

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Abstract

The invention belongs to the technical field of pattern recognition, and in particular relates to a composite gradient vector-based face recognition method. The method comprises the following steps of: marking a target area in a positioned face image, dividing feature subareas in the target area, performing orthogonal sampling by using marginal singular points of the feature subareas as starting points and end points of vectors to obtain base vectors, constructing all the base vectors in the target area into a vector cluster, performing multi-dimensional compounding on the base vectors to obtain all great gradient vectors in the vector cluster, constructing a composite gradient vector by using the great gradient vectors as elements, counting the dimension and the gradient information of the composite gradient vector, and comparing the composite gradient vector and the dimension and the gradient information of the composite gradient vector with a face library to recognize face identity. Compared with other face recognition methods, the face recognition method provided by the invention has the advantages of stronger environmental suitability and feature extraction capacity and high recognition performance under the conditions of illumination intensity variation, multiple gestures and multiple expressions and can be used for face recognition under the large-range complex environment in the field of biological feature identification.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, and in particular relates to a face recognition method based on compound gradient vectors. Background technique [0002] Face recognition technology uses computers to analyze and match face images, and has the technical advantages of no contact, moderate distance, and simple process. Face recognition is widely used, and has high application value in security fields such as criminal identification, identity tracking, entry and exit identity verification, and access control systems. It is also a classic research topic in the field of pattern recognition. [0003] As early as the late 1960s, people used the filtered geometric features of faces for classification and recognition, but the recognition effect was not ideal. In the late 1980s, Kirby[1] and others designed a face recognition technology based on the minimum mean square error description through the introduction of the K-L tran...

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Application Information

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IPC IPC(8): G06K9/00G06K9/64
Inventor 王志宏袁姮姜文涛
Owner LIAONING TECHNICAL UNIVERSITY
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