医用指纹模式识别——一种频域方法

F. You, Y.Q. Shi, P. Engler
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引用次数: 3

摘要

本文描述了一种将指纹自动分为三组的方法,即螺旋指纹、环状指纹和弓形指纹。它可以帮助医学科学家研究指纹模式与医学疾病(如乳腺癌)之间的关系。在研究中,提出了一种利用傅里叶谱特征的频域方法;也就是说,光谱中的突出峰给出了指纹模式的主方向。利用上述特征,得到了各子区域的主方向。然后可以确定整个图像的模式。频域方法可以更快地对螺旋进行分类,并且对指纹图像的质量不太敏感,但是当三叉区域太小时,它不容易对弓形和环状进行分类
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fingerprint pattern recognition for medical uses-A frequency domain approach
A method of automatically classifying fingerprints into three groups, whorl, loop, and arch is described. It can help medical scientists to study the relationship between fingerprint patterns and medical disorders, such as breast cancer. In the research, a frequency domain approach that uses the feature of Fourier spectrum was developed; that is, prominent peaks in the spectrum give the principal direction of fingerprint patterns. Using the above feature, the authors obtain the principal direction of every subregion. The pattern of the whole image then can be determined. The frequency domain approach allows one to classify whorl faster and is less sensitive to the quality of fingerprint image, but it does not easily allow for the classification of arch and loop when triradii areas are too small.<>
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