A False Fingerprint Detection Method Based on Fingerwave Transformation and SVM

Abstract

The invention discloses a false fingerprint detection method based on finger wave transformation and SVM, comprising the following steps: 1: collecting real and fake fingerprint images; 2: performing finger wave transformation on the collected real and fake fingerprint images; 3: extracting and collecting 4: Normalize the extracted eigenvectors; 5: Perform SVM training on the normalized eigenvectors to obtain classification based on support vector machine (SVM). Step 6: Use the SVM classification model obtained in Step 5 to classify the normalized feature vector of the fingerprint to be detected, and obtain a "true" or "false" SVM classification result. The invention extracts the feature vector after the fingerprint image is transformed by the finger wave, and inputs it into the support vector machine SVM for classification, and can distinguish the true and false fingerprints well under the condition of not changing the hardware of the fingerprint collecting instrument. The experimental results show that the present invention has high accuracy, low false rejection rate and false recognition rate, low cost and good practicability.

Description

technical field [0001] The design of the invention belongs to the field of image processing and pattern recognition, relates to a false fingerprint detection method, in particular to a false fingerprint detection method based on finger wave transformation and SVM. Background technique [0002] At present, fingerprint identification technology is widely used in various identification systems, and it has good advantages in terms of identification accuracy and operation convenience. [0003] However, many criminals use various materials to forge fingerprints to pass through the fingerprint identification system. True fingerprints are also called living fingerprints, which refer to the fingerprints of fingers with human biological characteristics, that is, the fingerprints of living human bodies. The corresponding fake fingerprints are also called dead body fingerprints, including fingerprints made of various materials, such as silica gel, clay, paper with printed fingerprint i...

AI Technical Summary

Problems solved by technology

However, in the current method of distinguishing true and false fingerprints, only some simple statistical characteristics and frequency domain characteristics are extracted. The method is too simple and cannot effectively distinguish true and false fingerprints.

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