Fingerprint identification model construction method, storage medium and computer equipment

Abstract

The invention provides a fingerprint identification model construction method based on Resnet and Triplet Loss, and the method comprises the steps: constructing N groups of initial samples; training Ngroups of initial samples by using Triplet Loss to obtain N groups of training samples; inputting the N groups of training samples into the initial Resnet model to train the initial Resnet model to obtain a to-be-tested target Resnet model; inputting the two groups of test samples into a to-be-tested target Resnet model for calculation to obtain two groups of image characteristic quantities; calculating the maximum cosine similarity between the two groups of image feature quantities by using a preset algorithm; judging whether the maximum cosine similarity is greater than or equal to a presetvalue or not; generating a target Resnet model according to the to-be-tested target Resnet model; or constructing M groups of initial samples and inputting the M groups of training samples into the to-be-tested target Resnet model to train the to-be-tested target Resnet model. The invention further provides a storage medium and computer equipment. According to the method, the problem of narrow-edge fingerprint matching identification is effectively solved through the fingerprint identification model constructed by Resnet and Triplet Loss.

Description

technical field [0001] The present application relates to the field of fingerprint identification, in particular to a method for constructing a fingerprint identification model, storage media and computer equipment. Background technique [0002] In today's society, with the continuous and rapid development of science and technology, mobile phones, computers and other electronic equipment are frequently updated, and the use of fingerprints for identity verification and identification has become popular. Fingerprint is a highly recognizable and unique human biological feature, and has the characteristics of easy collection and high security. Fingerprint identification is one of the main methods of current biometric identification technology. With the development of biometric technology, the fingerprint recognition technology under the screen has a tendency to change to the side fingerprint. Side fingerprint collection requires devices with smaller sensing area and more conven...

AI Technical Summary

Problems solved by technology

Side fingerprint collection requires devices with smaller sensing area and more convenient application. However, the collected fingerprint images are slender and strip-shaped, and there is little useful fingerprint information. The direction and position of entering and unlocking fingerprints may vary greatly. Bringing challenges to rejecting authenticity and identifying falsehoods in fingerprint identification

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