Fingerprint Recognition and feature extraction using transform domain techniques

Kavita Tewari, Renu L. Kalakoti
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引用次数: 14

Abstract

Fingerprint Recognition is one of the oldest and popular methods for person identification. There are two major approaches of fingerprint recognition namely image based and minutiae based. This paper presents an image based fingerprint recognition method. In this work first core point is detected and pre processing of image is done then transformation technique like Fast Fourier Transform (FFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Gabor Filter are used for feature extraction. These features consist of mean energy, standard deviation and Shannon entropy. The good recognition accuracy is achieved on the FVC 2002 database. Comparison of all the four transform is presented here and it is observed that DCT and DFT gives better result as compared to DWT and Gabor filter.
基于变换域技术的指纹识别与特征提取
指纹识别是最古老、最流行的身份识别方法之一。指纹识别主要有两种方法:基于图像的和基于细节的。提出了一种基于图像的指纹识别方法。首先对图像进行核心点检测和预处理,然后利用快速傅立叶变换(FFT)、离散余弦变换(DCT)、离散小波变换(DWT)和Gabor滤波等变换技术进行特征提取。这些特征包括平均能量、标准差和香农熵。在FVC 2002数据库上取得了较好的识别精度。本文对这四种变换进行了比较,发现与DWT和Gabor滤波器相比,DCT和DFT给出了更好的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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