基于卷积网络的唇印识别算法

Hongcheng Zhou
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引用次数: 0

摘要

身份信息安全面临着各种挑战,传统的身份识别技术已不能满足公共安全的需求。因此,有必要进一步探索和研究新的识别技术。针对唇印识别中图像预处理复杂、人工设计算法特征提取困难、准确率低等问题,提出了一种基于卷积神经网络的唇印识别方法,通过构建卷积神经网络LPRNet (lip print recognition network)。将得到的唇印图像输入到网络的训练识别模型中,简化唇印图像的预处理。通过特征信息提取和采样操作,减少了模型训练参数,克服了设计复杂特征提取算法的困难。通过对实验结果的分析和比较,获得了较高的识别率,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lip Print Recognition Algorithm Based on Convolutional Network
Identity information security is faced with various challenges, and the traditional identification technology cannot meet the needs of public security. Therefore, it is necessary to further explore and study new identification technologies. In order to solve the complex image preprocessing problems, difficult feature extraction by artificial design algorithm, and low accuracy of lip print recognition, a method based on the convolutional neural network is proposed, by building a convolutional neural network called LPRNet (Lip Print Recognition Network). The obtained lip print image is inputted into the training recognition model of the network to simplify the lip print image preprocessing. By extracting feature information and sampling operation, the model training parameters are reduced, which overcomes the difficulty of designing a complex algorithm to extract features. By analyzing and comparing the experimental results, a higher recognition rate is obtained, and the validity of the method is verified.
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