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Iris segmentation neural network model training method and iris segmentation method and device

A neural network model and training method technology, applied in the field of iris segmentation, can solve problems such as consuming large computing resources

Pending Publication Date: 2020-08-07
北京万里红科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, iris image segmentation based on deep learning iris segmentation technology will consume a lot of computing resources

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  • Iris segmentation neural network model training method and iris segmentation method and device
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  • Iris segmentation neural network model training method and iris segmentation method and device

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Embodiment Construction

[0036] The principle and spirit of the present disclosure will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present disclosure, rather than to limit the scope of the present disclosure in any way.

[0037]It should be noted that although expressions such as "first" and "second" are used herein to describe different modules, steps, data, etc. of the embodiments of the present disclosure, expressions such as "first" and "second" are only for A distinction is made between different modules, steps, data, etc., without implying a particular order or degree of importance. In fact, expressions such as "first" and "second" can be used interchangeably.

[0038] Iris image segmentation is an important part of iris recognition, which directly determines the performance of the entire iris recognition. Based on the traditional iris...

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Abstract

The invention relates to an iris segmentation neural network model training method and an iris segmentation method and device. The iris segmentation neural network model training method comprises thesteps: acquiring an iris recognition sample set, wherein the iris recognition sample set comprises a plurality of iris recognition samples, and the iris recognition samples comprise iris recognition tags; training an iris recognition network model based on a network automatic search technology and the iris recognition sample set; determining an iris segmentation neural network model, wherein the iris segmentation neural network model takes an iris recognition network model as a basic feature network; acquiring an iris segmentation sample set, wherein the iris segmentation sample set comprisesa plurality of iris segmentation samples, and the iris segmentation samples comprise iris segmentation labels; and training an iris segmentation neural network model based on the iris segmentation sample set. Through the method and the device, the consumption of computing resources can be reduced on the premise of ensuring the segmentation precision.

Description

technical field [0001] The present disclosure relates to the technical field of iris segmentation, in particular to a training method of a neural network model for iris segmentation, an iris segmentation method and a device. Background technique [0002] With the rise of artificial intelligence, biometric identification technologies such as face recognition, iris recognition, and fingerprint recognition have received great attention. Among them, iris recognition technology is considered to be one of the most stable, accurate and reliable verification methods. [0003] Iris image segmentation is one of the difficult problems in iris recognition. In order to be able to segment the iris in the iris image in complex and changeable scenes, at present, iris segmentation technology based on deep learning has emerged. However, iris image segmentation based on deep learning iris segmentation technology will consume a lot of computing resources. Contents of the invention [0004]...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06T7/11G06T7/136
CPCG06T7/11G06T7/136G06V40/18G06N3/045G06F18/214
Inventor 张小亮王秀贞戚纪纲杨占金其他发明人请求不公开姓名
Owner 北京万里红科技有限公司
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