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Collecting fingerprints for recognition using mobile phone cameras

机译:收集指纹以使用手机相机进行识别

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We present in this paper a sample quality control approach for the case using a mobile phone's camera as a fingerprint sensor for fingerprint recognition. Our approach directly estimates the maximum ridge frequency orientation by the amplitude-frequency features of the Fast Fourier Transform and takes the frequency features' difference in two perpendicular orientations as a distinguishing feature for ridge-like patterns. Then a decision criterion which combines the frequency components' energy and ridge orientation features is used to determine if an image block should be classified as high-quality fingerprint area or not. The number of such high-quality blocks can thus be used to indicate the whole fingerprint sample's quality. Experiments show this approach's effectiveness in distinguishing the high-quality blocks from other low-quality ones or background area. Mapping the quality metric to the sample utility as derived from the the NIST minutiae extractor "mindtct" function is also given to verify the approach's quality prediction effectiveness.
机译:我们在本文中介绍了一种使用手机的摄像头作为指纹识别指纹传感器的案例质量控制方法。我们的方法通过快速傅立叶变换的幅度-频率特征直接估计最大的脊波频率方向,并将两个垂直方向的频率特征之差作为类似脊波模式的特征。然后,将频率分量的能量和脊取向特征相结合的判定标准用于确定图像块是否应归类为高质量指纹区域。这样的高质量块的数量因此可以用来指示整个指纹样本的质量。实验表明,这种方法在区分高质量块与其他低质量块或背景区域方面是有效的。还提供了将质量度量映射到从NIST细节提取器“ mindtct”函数得出的样本实用程序的方法,以验证该方法的质量预测有效性。

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