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Monocular iris matching method based on feature point reprojection

A feature point and re-projection technology, which is applied to the acquisition/recognition of eyes, image data processing, instruments, etc., can solve the problems of time waste, wrong recognition, etc., and achieve the goal of improving efficiency, accuracy, accuracy and efficiency Effect

Active Publication Date: 2021-02-19
XIDIAN UNIV
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Problems solved by technology

Not only is this a waste of time, but, since these extra regions are likely to dilute the influence of the iris part on the final result, it will eventually lead to false recognition cases

Method used

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  • Monocular iris matching method based on feature point reprojection
  • Monocular iris matching method based on feature point reprojection
  • Monocular iris matching method based on feature point reprojection

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Embodiment Construction

[0031] Below in conjunction with accompanying drawing, specific embodiment of the present invention and effect are described in further detail:

[0032] refer to figure 1 , the present invention comprises the following steps:

[0033] Step 1: Obtain a monocular iris image I and perform data preprocessing on it.

[0034] refer to figure 2 , the specific implementation of this step is as follows:

[0035] (1.1) Adopt camera to take pictures of human eyes, obtain monocular iris image I;

[0036] (1.2) Adopt the method of Hough transform to carry out iris location to monocular iris image I, obtain iris region segmentation image I ', promptly adopt the method of Hough transform first, detect the iris border in the monocular iris image I, and the pixel outside the iris border The point gray value is set to 0; then the Hough transform method is used to detect the pupil boundary in the monocular iris image I, and the pixel gray value in the pupil boundary is set to 0 to obtain th...

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Abstract

The invention discloses a monocular iris matching method based on feature point reprojection. The problems that in the prior art, calculation time complexity is high, and matching results are affectedby areas outside irises are mainly solved. According to the scheme, the method comprises the steps: adopting a camera to acquire a monocular iris image, and sequentially processing iris positioning,feature extraction and boundary information elimination data preprocessing on the monocular iris image; an iris recognition database by using the iris region segmentation image after each time of preprocessing; acquiring a monocular iris image to be recognized by adopting a camera, and carrying out data preprocessing on the monocular iris image; matching the preprocessed iris region segmentation image B with an iris region segmentation image A in an iris recognition database, and estimating a homography matrix according to matched feature point pairs; re-projecting the feature points in the graph B to the space of the graph A, calculating the average position deviation of the corresponding feature points, and judging whether matching succeeds or not according to the average position deviation. According to the method, the iris region is segmented, the matching speed is increased while the matching accuracy is kept, and the method can be used for identity authentication.

Description

technical field [0001] The invention belongs to the field of computer vision image recognition, in particular to a single-eye iris matching method, which can be used for identity authentication in various scenarios where the identity of a target person needs to be judged. Background technique [0002] Iris recognition refers to the technology of collecting iris images of both eyes through special equipment and comparing the images with the existing data in the database to identify the identity information of the target person. At present, there are two mainstream iris recognition methods: iris recognition based on deep learning and iris recognition based on feature points. in: [0003] The iris recognition method based on deep learning is a data-driven recognition process, which enables the model to recognize iris characteristics in these states by adding eye deviation, posture changes, and image data samples with noise. However, this method has the problems of poor interp...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T7/11G06T7/136G06T7/40
CPCG06T7/11G06T7/136G06T7/40G06V40/19G06V40/193G06V40/197
Inventor 郑海红梁婕王义峰万波卢波李晟硕霍振峰
Owner XIDIAN UNIV
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