基于层次分析法的专家选择决策支持系统

M. Aziz, M. Aman
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引用次数: 12

摘要

面部识别是利用面部表情图片进行人类识别的过程。随着计算机的广泛使用,人们期望在这些智能设备上采用面部识别功能。随着面部识别方法的发现,采用过程成为可能,其中之一是主成分分析或更广为人知的PCA(主成分分析)。本研究首先使用Matlab编程语言设计了一个计算机程序。该程序是用来测试PCA方法使用一些面部图像。测试分为三类,分别是基于训练器图像的数量,基于关键向量特征的数量,以及阈值的确定。最后可以得出结论,PCA是一种很有价值的人脸识别方法。研究数据显示,在使用10个训练图像进行测试时,有一个相当好的引入结果,错误率相当小,这是20个测试中的一个错误引入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decision Support System For Selection Of Expertise Using Analytical Hierarchy Process Method
Facial recognition is the process of human identification using a picture of facial expression. With the widespread use of computers, it is expected that facial recognition capabilities can be adopted on such smart devices. The adoption process becomes possible with the discovery of facial recognition methods, one of which is the main component analysis or better known as PCA (Principal Components Analysis). The research started by designing a computer program using the Matlab programming language. The Program was used to test the PCA method using a number of facial imagery. Testing is divided into three categories, which are based on the number of the trainer image, based on the number of key vector features, and the determination of the threshold value. In the end it can be concluded that PCA is quite worthy to be a facial recognition method. The research Data shows a pretty good introduction result with a fairly small error rate on testing using ten training imagery, which is one error introduction of 20 Tests.
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