Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

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
View PDF7 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

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 even cause the recognition rate to drop for the input image that is quite different from the training image, and it takes a certain amount of time and effort. A certain number of pictures for training

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • 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

Examples

Experimental program
Comparison scheme
Effect test

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 ( - ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/40
Inventor 冯琰一张少文丁保剑
Owner PCI TECH GRP CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com