A Classification Method of Iris Image Quality Based on bp Network and Wavelet Transform

Abstract

The invention discloses a method for classifying iris image quality based on BP network and wavelet transform, including constructing a BP neural network model for iris image quality classification; selecting several iris image samples, performing wavelet transform on them, and extracting wavelet transform coefficients The eigenvalues ​​of the extracted wavelet transform coefficients are input to the BP neural network model for training; the trained BP neural network model is used to classify the iris image quality; the wavelet coefficient eigenvalues ​​extracted from the iris image samples are input to the trained BP Neural network model; if the output result of the BP neural network model is the same as the expected value of the available iris, it is judged that the current input iris quality is available; otherwise, if the output result is the same as the expected value of the unavailable iris, it is judged that the current input iris quality is not available.

Description

technical field The invention belongs to the field of image recognition, in particular to an iris image quality classification method based on BP network and wavelet transform. Background technique Iris recognition is a new biometric recognition method developed in recent years. Compared with other biometric identification methods such as fingerprint recognition, face recognition and voice recognition, iris recognition has stronger advantages in terms of accuracy, uniqueness, stability, collectability and non-invasiveness. In practical applications, the recognition effect of the iris recognition system is closely related to the quality of the collected images. Rainbow recognition system requires people to cooperate with equipment. However, there are some uncertain and unstable factors between equipment and people. In the process of iris image acquisition, uneven light conditions, changes in the distance between the human eye and the acquisition device, and the physiologic...

AI Technical Summary

Problems solved by technology

However, because the iris image is affected by contrast, illumination, interference, etc., there are some unstable features in the extracted iris feature template, which increases the difficulty of iris recognition.

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