DocumentCode :
3572634
Title :
Vehicle detection based on LBP features of the Haar-like Characteristics
Author :
Qiu Qin-jun ; Liu Yong ; Cai Da-wei
Author_Institution :
Inst. of Intell. Vision & Image Inf., China Three Gorges Univ., Yichang, China
fYear :
2014
Firstpage :
1050
Lastpage :
1055
Abstract :
To improve the adaptability of vehicle detection algorithms in complex traffic circumstances, a robust detection algorithm based on LBP features of Haar-like Characteristics was proposed. The image texture feature reflects some characteristics of the degree of gray distribution, contrast and spatial distribution, Haar-like was inducted into LBP, then this method calculate the local texture features of image in accordance with local binary pattern (LBP); then a small number of critical features from a large set of new haar local binary pattern was selected while training AdaBoost, finally two classes classification was performed using AdaBoost classifier and the selected features. Experimental results show that the robustness of the classifier has been greatly improved so that the classifiers can detect the vehicles accurately.
Keywords :
Haar transforms; image texture; learning (artificial intelligence); object detection; road vehicles; traffic engineering computing; AdaBoost classifier; Haar-like characteristic; LBP feature; contrast distribution; gray distribution; image texture feature; local binary pattern; robust detection algorithm; spatial distribution; vehicle detection; Automation; Educational institutions; Feature extraction; Intelligent control; Robustness; Support vector machines; Vehicle detection; AdaBoost classifier; Haar-like feature; LBP; vehicle detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
Type :
conf
DOI :
10.1109/WCICA.2014.7052862
Filename :
7052862
Link To Document :
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