High-precise palm-print identifying arithmetic based on single matching fractional layer combination

Abstract

The invention discloses a high-precise palm-print identifying method based on single matching fractional layer combination. firstly, the invention proposes a new palm-print image pre-processing method based on moving image method to positioning and partitioning the palm-print image for speeding up the pre-processing of the image; Then distantly filtering the palm-print image by the filter Gabor; directly filtering the sampling point by integrating the filtering step and the sampling step so as to greatly reduce the feature extracting time. During the matching identification, the vein information of the palm-prints towards the same direction is single operated Hamming matching, so the method solves the position excursion problem of the vein features towards different directions caused by different filters. The combination between the matching fractional layer and the average plan maximum remains and makes use of the phase and the direction information of the vein feature. the invention greatly speeds up the pre-processing of the palm-print image and the extraction of the vein feature and furthest enhances the ID identifying precision of the palm-print.

Description

technical field [0001] The invention relates to an identity authentication method based on biological features, specifically a high-precision palmprint recognition algorithm based on independent matching score layer fusion. technical background [0002] Accurate identification is required in daily life and in many occasions such as finance, justice, security check, e-commerce and so on. There are three main ways of human identification: the first is based on knowledge, such as using passwords, passwords, etc.; the second is based on items, such as using keys, ID cards, etc.; the third is based on the human body. Biometric methods, such as face, fingerprint, palm print, voice, etc. There are many defects in the first two methods. The method based on items is inconvenient to carry and is easy to be lost, damaged, stolen or forged; the method based on knowledge is easy to be forgotten and cracked. The identification method based on human biometrics overcomes the above-mention...

AI Technical Summary

Problems solved by technology

The computational complexity of the feature extraction stage of this algorithm increases significantly, and the four directional features are fused into one feature, which loses some useful palmprint information, making it difficult to make full use of the phase and direction information of the palmprint texture.

At the same time, due to the existence of the DC component in the Gabor filter, the extracted features are greatly affected by the light, which makes the recognition accuracy of palmprint authentication low.

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