Face identification method based on multiscale local phase quantization characteristics

A local phase quantization and face recognition technology, applied in the field of video recognition, can solve the problem of low stability

Inactive Publication Date: 2011-09-14
苏州市慧视通讯科技有限公司
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Problems solved by technology

The idea of ​​the method based on geometric features is to extract the relative position and relative size of the representative parts of the face (such as eyebrows, eyes, nose, mouth, etc.) Easily affected by factors such as light, expression, occlusion, etc., the stability is not high

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  • Face identification method based on multiscale local phase quantization characteristics
  • Face identification method based on multiscale local phase quantization characteristics
  • Face identification method based on multiscale local phase quantization characteristics

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specific Embodiment approach

[0023] ①A digital camera is used as a sensor to continuously collect fixed-point area images to form a digital video and convert it into a multi-frame continuous digital image. The digital camera adopts A / D chips such as CCD or CMOS; the video image acquisition device is installed directly in front of the monitored person;

[0024] 2. Apply the face detection algorithm to detect 1) the digital image to obtain a face image;

[0025] ③ Perform preprocessing such as normalization, scaling, and filtering on the face image described in ② and pre-process it to a fixed resolution;

[0026] ④ calculating the horizontal gradient image and the vertical gradient image of the specified face image described in ③;

[0027] 5. Calculate the integral image of the horizontal gradient image and the vertical gradient image described in ④;

[0028] ⑥ Obtain the face multi-scale local phase quantization (MLPQ) feature image set based on the integral image described in ⑤. The following explains ...

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Abstract

The invention discloses a face identification method based on multiscale local phase quantization characteristics. The face identification method is realized under the condition that a digital camera serves as a sensor and under the support of a digital signal processing chip. The face identification method is characterized by including the steps as follows: conducting pretreatment such as alignment, scaling, filtering and the like on a face image obtained by the digital camera; calculating a horizontal gradient image and a vertical gradient image; calculating an integral image to obtain an image set of multiscale local phase quantization characteristics of a face; preliminarily obtaining a candidate characteristic set by applying Adaboost characteristic selector; and obtaining a face characteristic vector in low dimensional space by utilizing multiple subspace linear discrimination analyzers, and matching the face characteristic vector with a pre-built face characteristic template to obtain the identity information of identify people. The face identification method has good identification rate, low misclassification rate and fast calculation speed, is especially suitable for embedded products and can be popularized and applied in a large scale.

Description

technical field [0001] The invention belongs to a video recognition method, in particular to a video recognition method applied to face recognition. Background technique [0002] Face recognition technology is one of the biometric technologies that are currently being vigorously developed. The face recognition system mainly includes data acquisition subsystem, face detection subsystem and face recognition subsystem. Face feature extraction is the most critical technology of the face recognition subsystem. A good face feature extraction technology will make the extracted face feature value smaller and better in discrimination performance, which can improve the recognition rate and reduce the false recognition rate. The existing face feature extraction methods mainly include: based on geometric features, based on subspace analysis, based on wavelet theory, based on neural network, based on hidden Markov model, based on support vector machine and based on 3D model. method. T...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/60
Inventor 刘宝赵春水刘文金
Owner 苏州市慧视通讯科技有限公司
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