Biometrics 简明教程

Pattern Recognition and Biometrics

模式识别涉及识别模式并再次确认。通常,模式可以是指纹图像、手写的草书单词、人脸、语音信号、条形码或互联网上的网页。

Pattern recognition deals with identifying a pattern and confirming it again. In general, a pattern can be a fingerprint image, a handwritten cursive word, a human face, a speech signal, a bar code, or a web page on the Internet.

各个模式通常根据其属性分为不同的类别。当具有相同属性的模式组合在一起时,结果组也是一个模式,通常称为模式 class

The individual patterns are often grouped into various categories based on their properties. When the patterns of same properties are grouped together, the resultant group is also a pattern, which is often called a pattern class.

模式识别是观察、区分感兴趣模式并对模式或模式类别做出正确判断的科学。因此,生物识别系统通过将一个人的特征与存储的模板进行比较来识别和分类 individuals。

Pattern recognition is the science for observing, distinguishing the patterns of interest, and making correct decisions about the patterns or pattern classes. Thus, a biometric system applies pattern recognition to identify and classify the individuals, by comparing it with the stored templates.

Pattern Recognition in Biometrics

模式识别技术执行以下任务 −

The pattern recognition technique conducts the following tasks −

  1. Classification − Identifying handwritten characters, CAPTCHAs, distinguishing humans from computers.

  2. Segmentation − Detecting text regions or face regions in images.

  3. Syntactic Pattern Recognition − Determining how a group of math symbols or operators are related, and how they form a meaningful expression.

下表突出显示了模式识别在生物特征识别中的作用 −

The following table highlights the role of pattern recognition in biometrics −

Pattern Recognition Task

Input

Output

Character Recognition (Signature Recognition)

Optical signals or Strokes

Name of the character

Speaker Recognition

Voice

Identity of the speaker

Fingerprint, Facial image, hand geometry image

Image

Identity of the user

Components of Pattern Recognition

模式识别技术将人类特征的随机模式提取成紧凑的数字签名,该数字签名可充当生物标识符。生物识别系统使用模式识别技术对用户进行分类并单独识别。

Pattern recognition technique extracts a random pattern of human trait into a compact digital signature, which can serve as a biological identifier. The biometric systems use pattern recognition techniques to classify the users and identify them separately.

模式识别的组成部分如下 −

The components of pattern recognition are as follows −

components of pattern recognition

最流行的模式生成算法如下 −

The most popular pattern generation algorithms are −

Nearest Neighbor Algorithm

您需要获取未知个体的向量,并计算其与数据库中所有模式的距离。最小的距离给出最佳匹配。

You need to take the unknown individual’s vector and compute its distance from all the patterns in the database. The smallest distance gives the best match.

Back-Propagation (Backprop) Algorithm

这是一个有点复杂但非常有用的算法,涉及大量的数学计算。

It is a bit complex but very useful algorithm that involves a lot of mathematical computations.