A new fingerprint image recognition approach using artificial neural network

In this article, the application algorithm in fingerprint image recognition based on artificial neural network and wavelet transform is put forward. In this algorithm, we have constructed a flatten-structure element utilizing the low-frequency parameters, which can affect the high-frequency parameters with the flatten-structure element. In this way we can enhance the fingerprint image with keeping the global texture feature of fingerprint. The experiment results indicate that this increase effect of image-pretreatment in fingerprint image recognition is good and the algorithm is effective.

I Introduction

The fingerprint recognition problem can be grouped into two sub-domains; fingerprint verification and fingerprint identification. In addition, different from the manual approach for fingerprint recognition by experts, the fingerprint recognition here is referred as AFRS (Automatic Fingerprint Recognition System), which is program-based. Fingerprint verification is to verify the authenticity of one person by his fingerprint. The user provides his fingerprint together with his identity information like his ID number. The fingerprint verification system retrieves the fingerprint template according to the ID number and matches the template with the real-time acquired fingerprint from the user. Usually it is the underlying design principle of AFAS (Automatic Fingerprint Authentication System).