人脸识别论文

中 文 摘 要

- I - 摘 要

人脸识别技术属于生物验证的一种，在身份验证领域日益发挥重要作用，具有十分广泛的应用前景。人脸检测和定位问题是人脸识别技术首先要解决的问题。人脸检测算法是一个高效的、自动的人脸识别系统中的关键技术之一。如今人脸检测问题已成为一个热门研究领域，新的算法不断被提出，不过由于人脸的复杂性，目前尚不能找到一个完美的算法。在不同应用环境下，有不同的算法，本文针对应用于视频中人脸检测问题进行了研究，论文的主要工作如下：

本文首先对人脸识别的任务提出了要求并阐述了其难点，结合其实现难度，提出一个能教快速的识别出图片中人脸的基于肤色的人脸检测算法，由于其一般适用性本文使用了RGB色彩空间，本算法将三维RGB空间映射为两维独立分布的空间。在二维空间下，肤色类聚性好且符合高斯分布，利用人工阈值法将肤色与非肤色区域分开，形成二值图像。

非肤色区域中依然有可能有部分区域颜色与肤色相近，所以阈值分割后的图像依然存有部分假肤色区域，经过形态学处理和限制长宽比之后，可得到人脸区域。

在确定人脸区域后，我们需要在原图上对人脸区域进行标记，这里可通过找到一些关键点，作出矩形框标记人脸区域

关键字:人脸识别,肤色检测,色彩空间,高斯分布，人脸检测 Abstract（英文摘要）

- II - Abstract

Face recognition technology is biological validation of an increasingly important

role in the field of authentication, a very wide range of applications. Face detection

and face recognition technology positioning problem is to be solved first. Face

detection algorithm is an efficient, one of the key technologies of automatic face

recognition system. Now face detection has become a hot area of research, new

algorithms constantly being made, but because of the complexity of the human face,

is still unable to find a perfect algorithm. In different environments, there are different

algorithms, this paper applies to video Face Detection conducted a study, the main

work of this thesis is as follows:

This paper proposes a face recognition task requirements and described its

difficulties, combined with the difficulty of its implementation, proposes a can teach

quickly identify the faces in the pictures Face detection algorithm based on skin color,

because of its general applicability as used herein, the RGB color space, this

three-dimensional RGB space mapping algorithm is a two-dimensional space of

independent distribution. In two-dimensional space, color clustering is good and in

line with the Gaussian distribution, the use of artificial threshold method to separate

color and non-color area, forming a binary image.

Non-skin area, there are still some regions may have similar color and skin

color, the image thresholding is still there after part false color region, after

morphological and restrictions aspect ratio obtained face region.

In determining the face region, we need to face in the picture area mark, there

may be some of the key points by finding made rectangle marked face region

Keywords: face recognition, color detection, color space, the Gaussian distribution,

face detection 目 录

- III - 目 录

摘 要 ......................................................................................................... I

ABSTRACT（英文摘要） ........................................................................... Ⅱ

目 录 ......................................................................................................... Ⅲ

第一章 绪 论 ............................................................................................ 1

第二章 需求分析 ......................................................................................... 3

2.1 任务概述 ........................................................................................................ 3

2.1.1 人脸识别完成的主要目标 ........................................................ 3

2.2 需求规定 ........................................................................................................ 3

2.2.1 对功能的规定........................................................................... 3

第三章 基于肤色检测的人脸识别及实现 ..................................................... 4

3.1 人脸肤色建模 ................................................................................................ 4

3.1.1 色彩空间 .................................................................................. 4

3.1.2 图片的修正处理 ....................................................................... 5

3.1.3 人脸肤色模型........................................................................... 5

3.1.4 特征的确定 .............................................................................. 13

3.2 各功能模块的实现 ........................................................................................ 14

3.2.1 打开图像模块........................................................................... 14

3.2.2 脸和头发识别模块 ................................................................... 16

3.2.3 标记模块 .................................................................................. 17

3.2.4 特征提取模块........................................................................... 24

附录 ............................................................................................................ 39

结束语 ......................................................................................................... 63