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Segmentation method of iris region in iris image based on Mask R-CNN neural network

An iris image and neural network technology, applied in the field of iris area segmentation, can solve the problem of not clearly locating the inner and outer boundary circles of the iris area, and achieve the effect of eliminating the preprocessing process, improving the accuracy and high precision.

Active Publication Date: 2019-07-26
DUKE KUNSHAN UNIVERSITY
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Problems solved by technology

However, the problem with such methods is that they do not explicitly locate the inner and outer boundary circles of the iris region

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  • Segmentation method of iris region in iris image based on Mask R-CNN neural network
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  • Segmentation method of iris region in iris image based on Mask R-CNN neural network

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[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0053] see Figure 1-5 , a method for segmentation of iris regions in an iris image based on Mask R-CNN neural network, comprising the following steps (flowchart see figure 1 ):

[0054] S100, establishing an improved Mask R-CNN neural network for iris segmentation, the input of the neural network is an iris image to be segmented;

[0055] S200, before training the neural network, label the sample iris image set for training, the labeling includes: 1) generating ...

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Abstract

The invention relates to the technical field of image segmentation, and provides a segmentation method of an iris region in an iris image based on a Mask R-CNN neural network which comprises the stepsof S100, S100, establishing an improved Mask R-CNN neural network for iris segmentation S200, before training the neural network, marking a sample iris image set for training; S300, respectively inputting the labeled sample iris images into a neural network, and training the neural network until convergence; S400, inputting the iris image that needs to be segmented by the iris region into the improved Mask R-CNN neural network that completes the training, and acquiring the double circle boundary information and the binary mask map of the iris region; and S500, completing iris segmentation according to the double-circle boundary information of the iris area obtained in the step S400 and the binary mask map. The invention realizes automatic learning to obtain a normalized iris image and aniris region binary mask by using the improved Mask R-CNN neural network in iris segmentation and localization. Accurate iris area double-circle boundary information can also be obtained, and subsequent iris recognition operation is facilitated.

Description

technical field [0001] The invention relates to the technical field of image segmentation, in particular to a method for segmenting an iris region in an iris image based on a Mask R-CNN neural network. Background technique [0002] With the continuous development of human science and technology, iris recognition technology has become more and more popular in people's daily life, and it has been successfully used in national security, border control, banking and finance, access control and attendance, and mobile terminals. For iris recognition technology, many technical challenges are encountered in practical application. Especially for scenes where people do not fully cooperate (that is, complex and uncontrollable scenes), the collected iris images of people have low resolution, high noise, squint, and blur due to changes in illumination and distance. and features such as occlusion. It is particularly difficult to accurately segment the iris area in the image, thereby affe...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V40/193G06V40/197
Inventor 冯春阳
Owner DUKE KUNSHAN UNIVERSITY
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