Hand back authentication method

Abstract

The invention discloses a hand back authentication method. The method is that a finger digital image and hand back vein are authenticated, wherein the finger digital image is the image obtained by positioning fixed handles of two axes at the center between a central part between horizontal shaft bars of an authentication device, inserting a middle finger between the two shaft, and shooting the connection range of the middle finger, the index finger, the ring finger and the hand back to obtain the image; the hand back vein is that reading the shot back digital image of the hand back; the hand back subcutaneous vein sample is extracted to confirm the user. According to the method, the variation of damaged fingerprint image, sweat, scar, decoration and other external environmental leads to low system performance and can be minimized, so that the system performance can be stabilized, and the convenience of the user can be ensured to the maximum; the system sensitivity and user rotating and moving can be determined according to the extremely small variation of the external environment and the input image, thus the mistaken rejection rate and mistaken recognizing rate can be decreased; the vein sample recognizing performance and system stability are improved regularly.

Description

technical field [0001] The invention relates to the field of physiological feature authentication, in particular to a hand back authentication method. Background technique [0002] Generally, to ensure the access control and security of large-scale users or small-scale users, security facilities and authentication systems for personal identification are required. This system uses magnetic card keys such as magnetic cards, RF cards, and smart cards. But, the personal identification mode that uses magnetic card key cannot fundamentally prevent card loss, embezzlement and misuse etc. In addition, when there are large-scale users, since the number of credit cards for personal payment is large, the disadvantage is that the financial burden is heavy. In order to improve this shortcoming, to authenticate the user himself, develop and use a physiological identification system, which can automatically identify and authenticate the user's own characteristics, confirm the user's ident...

AI Technical Summary

Problems solved by technology

This kind of dorsal vein distribution extraction algorithm has the following problems. In the obtained ROI image, the contraction and expansion of the vein sample are caused by the external temperature change. When the vein sample is extracted without considering the contraction and expansion phenomenon, most of the veins are lost in the distribution of the vein sample. Sample connectivity, cannot provide stable calculation performance

[0016] Furthermore, as the main reason for the low performance of the dorsal hand vein distribution extraction algorithm of the previous technology, there are the following problems: in the wide transition region of the passband, part of the boundary information between the vein sample and the background and the internal information of the vein sample are lost, and the vein to be extracted An important feature of the sample is venous sample connectivity, which loses some of its connectivity

[0017] Such problems, etc., will lead to serious performance degradation of system recognition performance.

Through the extraction algorithm of the vein distribution on the back of the hand, regardless of the thickness of the vein sample to be extracted, the vein sample is extracted with a single filter characteristic. The important feature of the vein sample to be extracted is the connectivity of the vein sample, which will lose part of its connectivity.

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