计算机工程Issue(3)：201-204,4.DOI:10.3969/j.issn.1000-3428.2014.03.042
改进型WLD与LBP特征融合的行人检测
Pedestrian Detection Fused with Improved WLD and LBP Feature
摘要
Abstract
This paper presents a feature fusion method(WLD-LBP) based on an improved Weber Local Descriptor(WLD) and Local Binary Pattern(LBP) through a two-dimensional discrete haar wavelet transform. The algorithm starts with a two-dimensional discrete haar wavelet for the image so as to obtain the subimages of four different frequencies. Making full use of the WLD and LBP, we extract the WLD characteristics of the low frequency part, and LBP features of the other three high-frequency portion, and then a vector consisted with the characteristics of the image is produced which we called WLD-LBP characteristics. Five groups of test experiments were conducted on INRIA Person databases using SVM as classifier,comparing with the characristics of WLD, Histogam of Oriented Gradient(HOG), PHOG and feature fusion of HOG-LBP,respectively. The results demonstrate the effectiveness with the highest recofnition rate up to 98.1%and robustness to illumination and noise of the proposed method.关键词
二维离散小波变换/特征融合/行人检测/WLD特征/LBP特征Key words
2-D discrete wavelet transform/feature fusion/pedestrian detection/Weber Local Descriptor(WLD)/Local Binary Pattern(LBP)分类
信息技术与安全科学引用本文复制引用
谭飞刚,殷苌茗,周书仁..改进型WLD与LBP特征融合的行人检测[J].计算机工程,2014,(3):201-204,4.基金项目
国家自然科学基金资助项目(60973113)；湖南省自然科学基金资助项目(12JJ6057)；湖南省标准化战略基金资助项目(2011031)；长沙市科技计划基金资助项目(K1203015-11)。 （60973113）
