DocumentCode :
1894426
Title :
An auto exposure control algorithm based on lane recognition for on-board camera
Author :
Tong Li ; Yan Song ; Tao Mei
Author_Institution :
Dept. of Intell. Vehicle Technol., Hefei Inst. of Phys. Sci., Hefei, China
fYear :
2015
fDate :
June 28 2015-July 1 2015
Firstpage :
851
Lastpage :
856
Abstract :
In order to obtain the accurate exposure time in real-time for an on-board camera in different urban environments, the proposed algorithm divides captured image into 5×5 sub-areas, calculates each sub-area´s average brightness value to get a histogram, analyzes the peak value distribution in histogram to determine what environments the automobile is in. According to the environment the automobile works in, the algorithm includes two modes: normal lit condition and high-contrast lit condition. It executes the appropriate exposure adjustment mechanism for two modes by analyzing their brightness distribution in different environments. To avoid the interference of other factors like the sky, the algorithm marks the road surface be the regions of interest in real time. Besides, the optimization goal is not mid-tone at all but the maximum difference between lane and background in the region of interest. The experimental results show that the algorithm can rapidly and stably switch exposure mode when the automobile is traveling in different road conditions, and it can get accurate exposure time in both modes fast and accurately.
Keywords :
automobiles; brightness; image sensors; object recognition; optimisation; traffic engineering computing; auto exposure control algorithm; automobile works; brightness distribution; captured image; exposure adjustment mechanism; exposure mode; high-contrast lit condition; lane recognition; normal lit condition; on-board camera; optimization goal; peak value distribution; road conditions; road surface; urban environments; Automobiles; Brightness; Cameras; Histograms; Intelligent vehicles; Roads; auto exposure; high-contrast; optimization; sub-area;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2015 IEEE
Conference_Location :
Seoul
Type :
conf
DOI :
10.1109/IVS.2015.7225791
Filename :
7225791
Link To Document :
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