计算机科学 ›› 2010, Vol. 37 ›› Issue (4): 293-.

• 图形图像及体系结构 • 上一篇    下一篇

基于两级分类器的人脸检测系统设计

张永,薛芝茂   

  1. (兰州理工大学 兰州730000)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受甘肃省自然科学基金(0809RJZA015 ,智能化的混合元搜索引擎研究)资助。

Face Detection System Design Based on Two Classifiers

ZHANG Yong,XUE Zhi-mao   

  • Online:2018-12-01 Published:2018-12-01

摘要: 人脸识别技术拥有广泛的应用前景,但是目前不少实现方式存在一些不尽人意之处。在对OPENCV与SVM分类器进行分析的基础上,阐述了基于两级分类器的人脸检测方法的原理和实现过程,首先分析了两级分类器的构建,引入人脸图像的矩形特征向量,将图像的矩形特征作为分类的依据,随后论述了系统设计与实现,包括灰度变换过程、直方图均衡过程、图像平滑过程以及金字塔序列化的实现。这种检测模式能够加快处理速度,提升效率。

关键词: 人脸检测,OPENCV , SVM分类器

Abstract: The face recognition technology has broad application prospects,but right now there are some failings in many implementations.Based on the analysis of OPENCV with the SVW classifier,this paper elaborated a strategy based on two-stage classifier of face detection principle and the implementation process.first,analysed two classifier construction,introduced a rectangular face image feature vector,used the image of the rectangular features as the basis for classification,and then discussed the system design and implementation,including the gray-scale transformation process,the process of histogram equalization,image smoothing serialization process as well as the relization of the pyramid.This test model can speed up the processing speed and has higher efficiency.

Key words: Human face detection,OPENCV,SVM classifier

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