Rapid iris detection method based on convolutional neural network

Abstract

The invention discloses a rapid iris detection method based on a convolutional neural network. The method comprises the following steps: (1) designing and training an iris detection network regressiondevice model; (2) obtaining a to-be-detected iris image and carrying out image preprocessing; (3) inputting the image obtained in the step (2) into the iris detection network regression device modelobtained in the step (1) to obtain the probability of belonging to the iris and the bias of the central point and the radius of the iris image; and (4) in order to obtain a more accurate iris position, outputting the iris center point and radius corresponding to the iris probability greater than a preset threshold in the result obtained in the step (3), and screening through a non-maximum suppression method to obtain the center point and radius of the iris of the final image, thereby obtaining the circular range corresponding to the iris area. According to the technical scheme, the compact convolutional neural network is adopted to carry out regression on the central point and radius offset of the iris image, the iris area is obtained according to the circular characteristics of the iris,the detection speed is high, the accuracy is high, and the method plays an important role in improving the iris recognition precision.

Description

technical field [0001] The invention belongs to the technical field of image processing and biometric information identification, and in particular relates to a fast iris detection method based on a convolutional neural network developed by embedding a neural network algorithm into a simulator for human iris image detection. Background technique [0002] The development of modern society has put forward higher requirements for the accuracy, security and usability of human identification. Identity recognition is a common problem encountered in people's daily life. Things such as the need to prove one's identity and identify others' identities often occur in life. The traditional identification method relying on photos has fallen far behind the requirements of the times, and human beings must seek new ways of identification that are safer, more reliable, and more convenient to use. The identification technology based on biometric identification has the following advantages: i...

AI Technical Summary

Problems solved by technology

[0004] Traditional iris detection methods mainly use the texture and grayscale features of the surrounding area of ​​the iris, and use methods such as edge detection, threshold segmentation, or local feature pattern (LBP) to detect the iris area. The detection of such methods is vulnerable to light, noise, and image blur. Influenced by factors, the stability is not high

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