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KAZE feature-based hand back vein recognition method

A vein recognition and hand back technology, applied in the field of image recognition, can solve the problem of low definition

Inactive Publication Date: 2019-08-23
LIAONING UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

[0003] It can be seen from related research that the recognition algorithm based on feature points can better meet the requirements of recognition accuracy and real-time performance at the same time, but for the poor image quality and low definition of hand vein images, how to retain The detailed information of the image, so as to obtain more accurate feature points still need further improvement

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  • KAZE feature-based hand back vein recognition method
  • KAZE feature-based hand back vein recognition method
  • KAZE feature-based hand back vein recognition method

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specific Embodiment

[0148] The performance of the recognition algorithm will be measured by the following three evaluation indicators: false recognition rate (False Accept Rate, FAR), false rejection rate (False Rejection Rate, FRR), and correct recognition rate (Genuine Accept Rate, GAR), as shown in formula (1) , formula (2), formula 3) shown.

[0149]

[0150]

[0151]

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Abstract

The invention discloses a KAZE feature-based hand back vein recognition method, which comprises the following steps of: 1, preprocessing an acquired hand back vein image, and carrying out feature point extraction on the preprocessed image based on a KAZE algorithm; step 2, performing coarse matching on the feature points extracted from the two images by using a nearest neighbor ratio method to obtain coarse matching feature points; and step 3, performing fine matching on the coarse matching feature points again by using an RANSAC algorithm to obtain matching points. The invention provides a KAZE feature-based hand back vein recognition method, which can significantly reduce the false recognition rate and the recognition time, and has good recognition accuracy and real-time performance.

Description

technical field [0001] It relates to the field of image recognition, in particular to a method for recognizing veins on the back of the hand with KAZE characteristics. Background technique [0002] At present, the research on vein recognition is mainly based on the multi-scale features of gray images and binary image features. Among them, the representative gray image multi-scale features include second-order wavelet transform, bandlet (Bandelet) decomposition contourlet (Curvelet) decomposition, Gabor decomposition, Gabor transform coding, SIFT feature points, SURF feature points, etc.; Value image features mainly include position of intersection and endpoint, structural relationship between feature points, binary vein curve information encoding, etc. Based on the above two thought recognition algorithms, they have achieved certain recognition effects to varying degrees. [0003] It can be seen from related research that the recognition algorithm based on feature points c...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/10G06V40/14G06F18/22
Inventor 王锦凯贾旭
Owner LIAONING UNIVERSITY OF TECHNOLOGY
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