基于变换特征的指纹匹配

M. Dale, M. Joshi
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引用次数: 16

摘要

在指纹识别应用中,利用更多的信息而不是细节是很有帮助的。本文提出了一种基于变换特征及其比较的指纹匹配方案。这里描述的技术避免了提取细节点来匹配指纹图像的需要。该方案采用离散余弦变换(DCT)、快速傅立叶变换(FFT)和离散小波变换(DWT)来生成指纹特征向量。找到核心点后,围绕核心点裁剪尺寸为64times64的指纹图像。变换应用于裁剪后的图像,没有任何预处理。变换系数按照特定的方式排列,用来获得以标准差表示的特征向量。指纹匹配是基于两个特征向量之间的最小欧氏距离。这里的数据库是通过使用500 dpi光学扫描仪捕获每人8张图像而形成的。用于形成特征向量的训练图像是每人2张、4张或6张。在匹配阶段,以识别方式检查所有图像或剩余图像,以找出百分比识别率。本文对这三种变换进行了比较,并观察到DCT和DFT比DWT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。
Fingerprint matching using transform features
In the fingerprint recognition application utilizing more information other than minutiae is much helpful. We present here a fingerprint matching scheme based on transform features and their comparison. The technique described here obviates the need for extracting minutiae points to match fingerprint images. The proposed scheme uses Discrete Cosine Transform (DCT), Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) to create feature vector for fingerprints. After finding out the core point, fingerprint image of size 64times64 is cropped around the core point. The transform is applied on the cropped image without any pre-processing. The transform coefficients are arranged in specific manner and are used to obtain the feature vector in terms of standard deviation. The fingerprint matching is based on the minimum Euclidean distance between two feature vectors. Here database is formed by capturing 8 images per person using 500 dpi optical scanner. Training images used to form feature vector are 2, 4 or 6 per person. In the matching phase either all or remaining images are checked in identification mode to find out the percentage recognition rate. Comparison for all the three transform is presented here and it is observed that DCT and DFT gives better result as compared DWT.
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