Face pore detection method based on deep neural network

A deep neural network and detection method technology, applied in the field of computer image processing, can solve the problems of face pore detection technology, such as missed detection rate, high false detection rate, and insufficient algorithm generalization ability, so as to reduce the misclassification rate and improve the detection rate. The effect of yield

Pending Publication Date: 2022-01-04
杭州颜云科技有限公司
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AI Technical Summary

Problems solved by technology

The invention overcomes the problems of the existing human face pore detection technology, such as high missed detection rate, high false detection rate, and insufficient generalization ability of the algorithm.

Method used

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  • Face pore detection method based on deep neural network
  • Face pore detection method based on deep neural network
  • Face pore detection method based on deep neural network

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Embodiment

[0042] Example: such as figure 1 As shown, a face pore detection method based on a deep neural network includes the following steps:

[0043] Step 1. Construct a face pore detection sample library, including the following process:

[0044] (1.1) Collect face images through a visible light high-definition camera. The face images are required to be front face images, with clear silhouettes and closed eyes. At least 200 front face images are collected. In the embodiment of the present invention, a total of 407 face images have been collected;

[0045] (1.2) Use manual marking to mark the face image described in step (1.1), and mark the image as pores and background regions respectively, so that the face image and its corresponding marking file can jointly constitute a face pore sample set, such as figure 2 It is a superimposed image of some human face skin images and pore samples selected from the human face pore sample database in the embodiment of the present invention, wher...

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Abstract

The invention relates to a face pore detection method based on a deep neural network, and the method comprises the steps of: firstly constructing a face pore sample detection data set, and employing a deep semantic segmentation network to detect face pores to obtain a preliminary pore detection result graph; then predicting a face partition through a deep semantic segmentation network, and performing post-processing on a partition graph; performing post-processing on the preliminary pore detection result image in combination with the face partition to obtain a final pore detection result; and on the basis, calculating the number of pores in each partition in combination with face partition and pore detection results. According to the invention, the problems of high omission ratio, high error detection rate, insufficient algorithm generalization ability and the like of the existing face pore detection technology are solved.

Description

technical field [0001] The invention relates to the technical field of computer image processing, in particular to a method for detecting human face pores based on a deep neural network. Background technique [0002] With the continuous development of social economy and the improvement of people's living standards, more and more people begin to pay attention to the skin quality of their faces, and one of the important indicators to measure the skin quality of the face is pores. Pore ​​detection can provide a basic data support for daily skin condition monitoring, cosmetics research and development, medical testing, medical cosmetology, etc. The pore detection method based on computer image processing technology is popular because of its convenient and quick characteristics. [0003] In the current pore detection methods involving the field of computer image processing technology, the data source can usually be obtained from daily mobile terminal equipment such as mobile pho...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06N3/04G06N3/08G06F18/243
Inventor 杨勤
Owner 杭州颜云科技有限公司
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