基于malsburg学习的改进BP网络旋转和位置不变指纹识别与定位

Sumana Kundu, G. Sarker
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引用次数: 8

摘要

本文设计并开发了一种改进的Malsburg学习和反向传播(BP)网络组合,用于识别和定位单个和多个指纹图像帧中的清晰指纹和遮挡指纹。目前的指纹识别方法是在一帧图像中实现不同指纹的完全旋转和位置不变性。利用Malsburg学习和BP网络相结合的方法对不同的指纹图像进行学习,然后对清晰和遮挡的图像进行识别和位置不变定位,是一种高效、有效、快速的方法。分类器的准确率、精密度、查全率和f值基本中等,指纹识别时间较低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A modified BP network using malsburg learning for rotation and location invariant fingerprint recognition and localization with and without occlusion
This present paper designs and develops a modified Malsburg Learning and Back Propagation (BP) Network combination for recognizing and localizing clear as well as occluded fingerprints in single and multiple fingerprint image frames. The present method of fingerprint recognition is completely rotation and location invariant of the different fingerprints in an image frame. The technique of using the combination of Malsburg learning and BP Network to perform learning of the different fingerprint images and subsequent identification and location invariant localization of clear and occluded images is efficient, effective and fast. Also the accuracy, precision, recall and F-score of the classifier are substantially moderate and the recognition time of fingerprints are quite low.
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