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Biological characteristic part image noise detection method

A technology of biometrics and detection methods, applied in image enhancement, image analysis, image data processing and other directions, can solve the problems of poor effect, serious time-consuming, and high complexity of detection schemes, achieving wide applicability of scenes and simple processing flow Efficient and fast evaluation of the effect of image quality

Active Publication Date: 2021-06-01
HANGZHOU HIKVISION DIGITAL TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the prior art, image noise detection and noise elimination are based on the global image, that is, all data information in the image is used for processing. This method is universal, but the effect is not good when applied to images of biological features , and some detection schemes with excellent effects are highly complex and time-consuming

Method used

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  • Biological characteristic part image noise detection method

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Embodiment 1

[0061] see figure 1 as shown, figure 1 It is a schematic flowchart of a facial image noise detection method in an embodiment of the present application.

[0062] Step 101, acquiring brightness image data including image data of a face as first image data,

[0063] Usually, the visible light (VIS) image is an RGB image including R, G, and B components. In order to avoid the judgment of the R, G, and B components in the RGB data from interfering with noise, the image will be realized by eliminating the hue and saturation information of the image while retaining the brightness. RGB images or color images are converted to grayscale images, that is, grayscale processing, and the specific conversion is:

[0064] Y=0.299*R+0.587*G+0.114*B

[0065] Among them, Y is the gray value of the image, and R, G, and B are the components of the RGB image.

[0066] For near-infrared (NIR) images, usually 8-bit single-channel data, that is, Y data, no conversion is required. .

[0067] Step...

Embodiment 2

[0105] see Image 6 as shown, Image 6 It is a schematic flowchart of a facial image noise detection method according to another embodiment of the present application.

[0106] Step 601, removing at least the areas including eyes, nose, and mouth in the face image to extract an effective area image of the face,

[0107] In view of the severe interference caused by the eyes, nose, and mouth regions to the noise calculation, the regions consisting of the eyes, nose, and mouth are removed. See 7a and Figure 7b as shown, Figure 7a and Figure 7b It is a schematic diagram of the remaining effective area after removing the area based on the face image. like Figure 7a Among them, the removal area includes a horizontal strip-shaped area that runs through the eyes, and a vertical strip-shaped area that is perpendicular to the horizontal strip-shaped area and covers the nose and mouth, wherein the width of the horizontal strip-shaped area is at least the left outer corner of th...

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Abstract

The invention discloses a biological characteristic part image noise detection method, which is characterized in that the method comprises the following steps: based on a biological characteristic part image, image data in an effective area is extracted to obtain effective area image data, and the effective area comprises the biological characteristic part image except an area which interferes with noise judgment; and carrying out convolution calculation on pixel values of pixels in the effective region image data and a convolution kernel to obtain convolution values, calculating an average value of the convolution values to obtain a noise degree representing image noise of the biological feature part, If the noise degree is greater than a preset noise threshold, judging that the biological feature part image is a noise image. According to the method, the noise degree of the effective area can be quickly calculated on the basis of a single-frame image, the processing flow is simple and efficient, and the scene applicability is very wide.

Description

technical field [0001] The invention relates to the field of digital image processing, in particular to a method for detecting image noise of biological feature parts. Background technique [0002] Image noise refers to unnecessary or redundant interference information in image data, such as "snowflake" noise that is usually generated in the case of insufficient light. The existence of noise seriously affects the image quality and must be corrected before image enhancement and classification. [0003] As one of biometric identification, face, palmprint, fingerprint, etc. have been widely used. Taking facial images as an example, the quality of facial images has a direct impact on the actual effects of face detection algorithms, face recognition algorithms, and face liveness detection algorithms, and is also related to the operation of auxiliary modules, such as exposure control and gain control. , wide dynamic settings, etc., one of the most important criteria for judging ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06T5/00G06T5/40
CPCG06T5/40G06T2207/30201G06T2207/10004G06V40/165G06V40/171G06T5/94G06T5/70
Inventor 华丛一任志浩
Owner HANGZHOU HIKVISION DIGITAL TECH
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