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Signature fingerprint identification method

A recognition method and fingerprint technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as low efficiency, and achieve the effect of reducing time, high detection performance and comparison accuracy, and enhancing accuracy

Active Publication Date: 2021-06-22
HANGZHOU JINGLIANWEN TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

This process not only relies on expensive equipment, but also takes a lot of time and labor to mark the details, which is very inefficient

Method used

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with the accompanying drawings.

[0048] refer to Figure 1 ~ Figure 3 , a method for identifying a signature fingerprint, the method comprising the following steps:

[0049] 1) Register the rolling fingerprint to the signature fingerprint, and use the Gabor-enhanced fingerprint minutiae point extraction algorithm to extract the direction field and minutiae of the rolling fingerprint as the weak label of the signature fingerprint;

[0050] 2) Using the weak label of the signature fingerprint as the training label, a fully convolutional neural network model that simultaneously generates signature fingerprint enhancement maps and minutiae points is obtained;

[0051] 3) Perform minutiae coding and texture coding on the generated signature fingerprint enhancement map and minutiae points, and then compare them, and then perform strategy fusion on the compared scores to obtain the final comparison score of...

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Abstract

A signature fingerprint identification method comprises the following steps: 1) registration of a signature fingerprint and a rolling fingerprint and manufacturing of a weak label: registering the rolling fingerprint with the signature fingerprint, and extracting a direction field and minutia points of the rolling fingerprint by using a traditional algorithm to serve as the weak label of the signature fingerprint; 2) training a multi-task full convolutional neural network based on signature fingerprint image enhancement of a weak label and minutiae extraction, taking the weak label of the signature fingerprint as a training label, and obtaining a full convolutional neural network model which simultaneously generates a signature fingerprint enhancement image and minutiae; and 3) performing multi-score strategy fusion based on the minutiae template and the texture template, performing minutiae coding and texture coding on the generated signature fingerprint enhanced graph and the minutiae, performing comparison, and performing strategy fusion on the compared scores to obtain the final comparison score of the fingerprint. According to the invention, specialists do not need to manually mark fingerprint minutia points, a large amount of time and labor cost are saved, and the comparison accuracy is high.

Description

technical field [0001] The invention relates to image processing, machine learning, deep learning, fingerprint identification and other field knowledge, and mainly introduces a method for processing and comparing signature fingerprints. Background technique [0002] A contract is an agreement between civil subjects to establish, modify, and terminate a civil legal relationship, and it is the main manifestation of the autonomy of private law. The two parties who sign the contract need to leave information that can prove their personal identity on the contract, the most commonly used of which are signature, seal and fingerprint. Signatures can reflect personal identity to a certain extent, but there are some disadvantages in using signatures to prove the identity basis on the contract. First of all, there are signs and impostors in real life, which greatly affect the reliability of the signature; second, the name may not uniquely determine a person's identity, and some people...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/13G06V40/33G06V10/25G06N3/045G06F18/22
Inventor 张永良谢蔚李志伟黄聪敏
Owner HANGZHOU JINGLIANWEN TECH
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