Fingerprint Recognition Based on Wavelet Transform and Ensemble Subspace Classifier

Andres Rojas, G. Dolecek
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引用次数: 1

Abstract

This paper presents a fingerprint recognition system based on Wavelet transform, multiple domain feature extraction, and Ensemble Subspace Discriminant Classifier. The main contribution of this work is the computation of a set of features that can be used for the classification of fingerprints, and the implementation of an ensemble of discriminant classifiers. First, the review of previous works is presented. Next, a detailed description of the proposed method is elaborated. Finally, it is shown that the proposed system provides the highest accuracy (97.5%) in comparison with other works proposed in the literature using a different type of classifier such as the ensemble subspace discriminant.
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基于小波变换和集合子空间分类器的指纹识别
提出了一种基于小波变换、多域特征提取和集成子空间判别分类器的指纹识别系统。这项工作的主要贡献是计算了一组可用于指纹分类的特征,并实现了一个判别分类器的集成。首先,对前人的研究进行了回顾。接下来,对所提出的方法进行了详细的描述。最后,与文献中使用不同类型的分类器(如集合子空间判别器)的其他作品相比,所提出的系统提供了最高的准确率(97.5%)。
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