Face image denoising method on basis of noise evaluation model

A face image and evaluation model technology, which is applied in the field of face image denoising, can solve problems such as noise and recognition rate decline, and achieve the effect of simple algorithm principle, improved efficiency and effect, and good adaptability

Inactive Publication Date: 2014-11-19
PCI TECH GRP CO LTD
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Problems solved by technology

This method uses the noise-free face image to train the feature space, and the effect is better for the input image that is similar to the training image, but it is easy to introduce a lot of noise and

Method used

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  • Face image denoising method on basis of noise evaluation model
  • Face image denoising method on basis of noise evaluation model
  • Face image denoising method on basis of noise evaluation model

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specific Embodiment approach

[0017] (1) To grayscale the input image, use the Adaboost classifier based on Haar features to detect faces;

[0018] (2) Attachment figure 1 , Use the active shape model to extract 68 feature points of the face and divide the face into nine regions, which are the forehead region, the left and right eyebrow regions, the left and right eye regions, the nose region, the left and right face regions, and the mouth region;

[0019] (3) Attachment figure 2 , In each of the nine regions of the face, the Canny operator is used to extract edges, and the edges whose length is greater than T1 are retained, and the noise density value k of each region is obtained according to the area ratio of the edges. i ;

[0020] (4) According to the noise density value k of each area i Determine the parameters of the bilateral filtering algorithm and have a proportional relationship. The formula for bilateral filtering is as follows:

[0021] ω ( i , j , k , 1 ) = exp ( - ...

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Abstract

The invention provides a face image denoising method on the basis of the noise evaluation model and application thereof in face recognition. The method is used for achieving the purposes of noise cancellation and self-adaptive parameter training by noise analysis and processing on a face image obtained through the face detection technique. A face image is divided into 9 areas in the algorithm with the utilization of the active shape model; the noise density distribution diagrams are obtained when the face image noise is calculated by adopting a noise evaluation model on each area; that the useful texture information in the face is better protected is guaranteed when the self-adaptive bilateral filtering algorithm is carried out according to the noise density distribution diagram of each area. The face image denoising method effectively solves the problem that the recognition rate is greatly decreased due to uneven noise in the face recognition process, so that the recognition performance of face recognition is improved.

Description

Technical field [0001] The invention relates to the field of computer vision, in particular to a method for denoising a face image. Background technique [0002] Face recognition is an important research field in recent years. Although great progress has been made, in some practical applications, many factors such as noise, light, posture, etc. affect the recognition effect to varying degrees. Among them, noise is more common. A factor of influence. [0003] At this stage, the most commonly used face image denoising method is principal component analysis denoising method. This method uses noise-free face image training feature space, which is better for input images that are similar to the training image, but for input images that are larger and different from the training image, it is easy to introduce a lot of noise and even cause the recognition rate to drop, and it takes time and A certain number of pictures for training. Summary of the invention [0004] The invention provid...

Claims

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Application Information

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IPC IPC(8): G06K9/40
Inventor 冯琰一张少文丁保剑
Owner PCI TECH GRP CO LTD
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