基于局部自我相关函数光线照明变化下的人脸检测

山东大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (5): 59-64.

基于局部自我相关函数光线照明变化下的人脸检测

朱洪锦1,范洪辉1,陈兴瑞1,田村安孝2

1.江苏技术师范学院计算机工程学院, 江苏常州 213001; 2.日本山形大学大学院理工学研究科, 山形米泽 9928510

收稿日期:2012-05-10 出版日期:2012-10-20 发布日期:2012-05-10
作者简介:朱洪锦(1981- ),女,吉林柳河人,讲师,主要研究方向为数字图像处理,模式识别,人脸检测等. E-mail: zhuhongjin@jstu.edu.cn
基金资助:
江苏技术师范学院科研启动基金资助项目(KYY11048,KYY11049)

Image normalization based on local autocorrelation and its application to face detection

ZHU Hong-jin1, FAN Hong-hui1, CHEN Xing-rui1, TAMURA-Yasutaka2

1.College of Computer Engineering, Jiangsu Teachers University of Technology, Changzhou 213001, China; 2.Graduate School of Science and Engineering, Yamagata University, Yonezawashi Yamagata 9928510, Japan

Received:2012-05-10 Online:2012-10-20 Published:2012-05-10

摘要/Abstract

摘要： 针对照明变化条件下人脸图像检测精度相对较低的问题,以照明变化下的人脸检测为研究对象,提出局部自我相关函数(local autocorrelation, LAC),研究基于Adaboost算法下采用局部自我相关函数为前处理的光照变化下人脸检测。提出了局部自我相关函数定义模型,对局部自我相关函数的物理特性进行分析,从理论上验证局部自我相关函数对线性照明变化的鲁棒性。采用卡内基梅隆大学的人脸照明变化数据库(CMU PIE Database)作为检测数据验证基于局部自我相关函数的光线照明变化下的人脸检测,实验结果证明了局部自我相关函数消除照明变化对人脸检测精度影响的有效性。

Abstract: Nonuniformity of luminance in images due to irregular lighting etc. could cause difficulties in various kinds of image processing in face detection. A normalization method was presented for recognizing human faces under variation in lighting, which was called local autocorrelation (LAC) method. LAC method was applied to human face detection based on Adaboost algorithm. The classification result of CMU PIE database for original and LAC images were compared with the LAC method. The physical properties of the LAC were analyzed, and the LAC robustness of linear changes in illumination was verified theoretically. Experimental results showed the number of weak classifiers could be reduced to a great extent, while preserving equal detection capability. The effectiveness of elimination of nonuniform illumination variation in images was verified in face detection experiment.

Key words: local autocorrelation, illumination variation, image preprocessing, face detection, Adaboost algorithm

中图分类号:

TP391.4

朱洪锦1,范洪辉1,陈兴瑞1,田村安孝2. 基于局部自我相关函数光线照明变化下的人脸检测[J]. 山东大学学报(工学版), 2012, 42(5): 59-64.

ZHU Hong-jin1, FAN Hong-hui1, CHEN Xing-rui1, TAMURA-Yasutaka2. Image normalization based on local autocorrelation and its application to face detection[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2012, 42(5): 59-64.

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