Palm grain identification method based on direction character

Abstract

The invention discloses a method for identifying the palmprint based on directional characteristic, including the steps of: collecting the palmmprint image, preprocessing palmmprint image, constructing the palmmprint trainning ROI image collection, extracting-establishing the palmmprint direction feature coding RPOC by the palmmprint feature, matching the palmmprint in the dot pairs area. First new palmmprint trainning ROI image is established by rotating the palmmprint trainning ROI image and is added into the palmmprint trainning ROI image collection for compensating the rotation error; secondly, a modified limited Radon conversion MFRAT is designed, and the palmmprint direction characteristic mode is obtained by comparing the energy sizes of linear areas in six direction at the local area of palmmprint image; Finally, the palmmprint direction characteristic mode is matched through the match of dot pair area. The palmmprint direction feature coding RPOC in the method, not only can reflect the structural feature of palmprint, also can carry major distinguishing information, at the same time, having good fault-tolerant ability for light change, displacement revolving between palmmprint images or the like.

Description

[0001] Field [0002] The invention relates to a method for identity authentication using human biological features, in particular to a palmprint recognition method based on direction features. Background technique [0003] In the network information society, there is an urgent need to be able to effectively identify people's real identities. There are two main traditional identification methods: one is password-based security mechanism; the other is certificate-based security mechanism. However, these traditional confirmation mechanisms have their inherent drawbacks. For example, multiple passwords are difficult to remember and easy to forget; certificates are easy to be forged, stolen and lost. Therefore, people look forward to using a safer and more convenient identity authentication method. [0004] In the past ten years, the identity authentication technology (Biometrics) based on human body biometrics has been paid more and more attention by people. The so-called bio...

AI Technical Summary

Problems solved by technology

[0012] Among the above recognition methods, the first type of texture-based method was studied relatively early, but this method is easily affected by factors such as illumination changes, and the recognition rate is difficult to improve.

The second type of line-based methods are subject to many limitations, for example, many palm lines are blurred and difficult to extract

The third type of recognition method based on subspace technology is currently a research hotspot, but this method only considers the correlation between image pixels and does not use the structural information of palmprint images, and the recognition results on large-scale databases still need further research. verify

[0015] However, the palmprint recognition method based on CompetitiveCode still has some deficiencies

The specific performance is as follows: (1) the Gabor filter used in the palmprint recognition method of CompetitiveCode is not the best tool for extracting the directional features of the palmprint image; (2) the feature extraction speed is relatively slow, because the Gabor filter with a larger template is used Filtering the palmprint image is time-consuming; (3) No solution to the rotation problem is proposed, and the recognition rate is difficult to further improve; (4) CompetitiveCode's palmprint recognition method uses Hamming distance for matching and lacks good fault tolerance

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