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A novel method for fingerprint feature extraction

机译:一种新的指纹特征提取方法

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摘要

Fingerprint recognition is a method of biometric authentication that uses pattern recognition techniques [1] based on high-resolution fingerprints images of the individual. Fingerprints have been used in forensic as well as commercial applications for identification as well as verification. The fingerprint surface is made up of a system of ridges and valleys. The steps for Fingerprint recognition include image acquisition, preprocessing, feature extraction and matching [2]. In the present work, a new fingerprint feature detection algorithm has been proposed. It has been found that presence of noise in fingerprint images leads to spurious minutiae. To overcome this problem, feature extraction has been done which efficiently determine the minutiae points in fingerprint [1]. The proposed method can be used in matching the template for finding bifurcation and termination. The new smoothing algorithm is proposed for the detection of the features of fingerprints. A method has been introduced for finding ridges in the fingerprint image with the help of eight different masks. It is a process of making a binary image of ridges from the grayscale fingerprint image. The experimental results showed the accuracy of the algorithm in terms of genuine acceptance rate, false rejection rate, false acceptance rate.
机译:指纹识别是基于个体的高分辨率指纹图像使用模式识别技术[1]的生物认证方法。指纹已用于法医以及商业应用,用于识别和验证。指纹表面由脊和山谷系统组成。指纹识别的步骤包括图像采集,预处理,特征提取和匹配[2]。在本作工作中,已经提出了一种新的指纹特征检测算法。已经发现指纹图像中的噪音存在导致杂散的细节。为了克服这个问题,已经完成了特征提取,从而有效地确定指纹中的细节点[1]。所提出的方法可用于匹配模板以寻找分叉和终止。提出了新的平滑算法来检测指纹的特征。已经引入了一种方法,用于在八个不同的面具的帮助下找到指纹图像中的脊。它是从灰度指纹图像制作脊的二进制图像的过程。实验结果表明,在真正接受率,假拒绝率,假验收率方面的算法精度。

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