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A Segmentation System for Iris Localization Based on Hole Residual Attention Structure

A technology of iris positioning and attention, applied in the direction of neural architecture, instruments, biological neural network models, etc., to achieve the effect of realizing the quality of iris area

Active Publication Date: 2022-03-15
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0009] The technical problem to be solved by the present invention is to provide an iris image segmentation system aimed at solving iris positioning and segmentation under complex conditions

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  • A Segmentation System for Iris Localization Based on Hole Residual Attention Structure
  • A Segmentation System for Iris Localization Based on Hole Residual Attention Structure
  • A Segmentation System for Iris Localization Based on Hole Residual Attention Structure

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Embodiment Construction

[0027] 1. Structural design

[0028] In order to better perform iris segmentation, this paper proposes a spatial attention mechanism to improve segmentation performance. The specific attention structure is as follows: figure 2 shown. In order to avoid the problems caused by direct channel compression, the attention mechanism proposed in this paper first performs global pooling on the feature map, for a dimension of After the feature tensor of the global pooling is obtained, the dimension is , and then use the two-layer fully connected network to obtain the channel mask vector. The two-layer fully connected network implements the mapping process. After the channel mask is obtained, the channel-weighted feature map is obtained by multiplying the corresponding channels, and then the feature map channel is compressed to 1 using a convolution operation with a convolution kernel of 1×1. Expand the compressed single-channel feature map into a vector form to obtain a spatia...

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Abstract

The invention provides an iris localization and segmentation system based on a hole residual attention structure, which includes a feature extraction structure, a segmentation structure and a scoring structure; The output is respectively related to the input of the scoring structure and the input of the segmentation structure; the segmentation structure includes M-1 upsampling modules and M-2 feature fusion modules that are connected in series at intervals, and the output of the i-th feature extraction module is to the M-i-th The first level feature fusion module has one input, and the other input of the feature fusion module is connected to the output of the upsampling module of this level, and the M-1st level upsampling module outputs the mask image after segmentation. The feature extraction module includes N hole attention residual structure DARB and 1 down-sampled hole attention residual structure DADRB. The invention uses DARB to build a neural network, realizes accurate and rapid iris area division by designing a multi-branch network, and realizes automatic evaluation of the quality of the iris area.

Description

technical field [0001] The invention belongs to the field of digital image processing and machine learning, and is mainly used for iris image detection and segmentation. Background technique [0002] Iris recognition is a biometric recognition technology that uses the characteristic points formed by the internal fibrous tissue of the biological iris to verify and identify people's identities. Because the iris has high stability, uniqueness, anti-counterfeiting and other excellent properties. Compared with other biometric identification methods, iris verification has higher recognition accuracy and is therefore more widely used. [0003] The iris recognition process generally consists of preprocessing, iris location, feature extraction, and feature matching. The iris location and segmentation algorithm is the most important part of iris recognition, and the inaccurate iris location area will directly affect the accuracy of subsequent feature extraction, resulting in a decli...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V40/18G06V10/26G06V10/82G06N3/04
CPCG06V40/18G06V10/267G06N3/045
Inventor 解梅赵雷廖炳焱钮孟洋
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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