采用图像直方图特征函数的高速相机自动曝光方法

马泽龙; 高慧斌; 余毅; 蔡立华

doi:10.3788/OPE.20172504.1026

您当前的位置：

首页 >

文章列表页 >

采用图像直方图特征函数的高速相机自动曝光方法

信息科学 | 更新时间：2020-07-07

- 采用图像直方图特征函数的高速相机自动曝光方法
- Auto exposure control for high frame rate camera using image histogram feature function
- 光学精密工程 2017年25卷第4期页码：1026-1035
- 作者机构：
  
  1.中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
  2.中国科学院大学, 北京 100039
- 作者简介：
  
  马泽龙 (1985-), 男, 吉林长春人, 博士研究生, 2008年、2013年于长春理工大学分别获得学士、硕士学位, 主要研究方向为高速相机的自动调光调焦。E-mail:mazelong1985@126.com MA Ze-long, E-mail:mazelong1985@126.com
  [ "高慧斌 (1963-), 男，吉林长春人，研究员，博士生导师，1985年、1990年于吉林工业大学分别获得学士、硕士学位，主要研究方向为光电测量和跟踪控制技术。E-mail:gaohuibin@163.com" ]
- 基金信息：
  
  国家863高技术研究发展计划资助项目(2011AA8082035)
- DOI：10.3788/OPE.20172504.1026
  中图分类号： TP391.4
- 收稿日期：2016-08-04，
  
  录用日期：2016-10-12，
  
  纸质出版日期：2017-04-25
- 稿件说明：
移动端阅览
马泽龙, 高慧斌, 余毅, 等. 采用图像直方图特征函数的高速相机自动曝光方法[J]. 光学精密工程, 2017,25(4):1026-1035.

Ze-long MA, Hui-bin GAO, Yi YU, et al. Auto exposure control for high frame rate camera using image histogram feature function[J]. Optics and precision engineering, 2017, 25(4): 1026-1035.
马泽龙, 高慧斌, 余毅, 等. 采用图像直方图特征函数的高速相机自动曝光方法[J]. 光学精密工程, 2017,25(4):1026-1035. DOI： 10.3788/OPE.20172504.1026.

Ze-long MA, Hui-bin GAO, Yi YU, et al. Auto exposure control for high frame rate camera using image histogram feature function[J]. Optics and precision engineering, 2017, 25(4): 1026-1035. DOI： 10.3788/OPE.20172504.1026.

摘要

提出一种采用图像直方图特征（Histogram Feature，HF）函数的自动曝光方法，用于在背景光照快速、大范围变化的情况下对高速相机进行自动曝光控制。首先，采用多点测光对获取的图像进行兴趣区域（Region of Interests，ROIs）提取，以降低系统测光的计算量。然后，通过计算兴趣区域的HF函数选取大步长对曝光时间进行粗调。最后，通过模糊逻辑计算出曝光时间的精调步长并运用阈值限制实现变步长搜索最佳曝光时间，提高高速相机自动曝光的准确性及稳定性。实验结果表明：本文方法可以在2 ms内完成一帧图像的亮度测量并对曝光时间进行调整，相较于基于平均亮度值的传统自动曝光方法，在0~110 ms内，光源光照强度从760~23 100 lux反复变化时，本文方法获得的图像信息熵比平均亮度值法的信息熵均值提高48.38%，方差降低62.13%，可以提供更好与更稳定的图片细节信息，为后续的自动调焦、图像识别以及目标跟踪提供参考。

Abstract

In this paper

a method for auto exposure based on image HF (Histogram Feature) function was proposed to achieve auto exposure control on high-speed camera under the condition where the background lumination was in fast speed and wide-range changes. First

multi-point photometry was conducted to extract the Regions Of Interest (ROI)

thus lowering calculation amount of the photometric system; then

large step size was selected to carry out coarse adjustment of the exposure time by calculating HF function of these ROIs; finally

accurately-adjusted step size of the exposure time was calculated through fuzzy logic and then the optimal exposure time was achieved through variable-step search by using threshold limit

so accuracy and stability of the high-speed camera auto exposure were improved. The resuts show that proposed method is able to complete brightness measurement of one frame image as well as an adjustment in the exposure time within 2 ms; and compared with traditional auto exposure method based on average brightness

average information entropy achieved by proposed method is improved by 48.38% within 0-110 ms when the illumination intensity varies repeatedly from 760 lux to 23 100 lux

with a variance decreased by 62.13%. This method can provide better and more stable details on the image

which serves as useful reference for follow-up auto focusing

image recognition and target tracking.

关键词

Keywords

references

KUNO T, SUGIURA H, MATOBA N. A new automatic exposure system for digital still cameras[J]. IEEE Transactions on Consumer Electronics , 1998, 44(1):192-199.

CHO M, LEE S, NAM B D. Fast auto-exposure algorithm based on numerical analysis[C]. Electronic Imaging'99, International Society for Optics and Photonics, San Jose, California , 1999:93-99.

MURAKAMI M, HONDA N. An exposure control system of video cameras based on fuzzy logic using color information[C]. Fifth IEEE International Conference on Fuzzy System ( Volume :3), New Orleans , LA:IEEE , 1996, 3:2181-2187.

LEE J S, JUNG Y Y, KIM B S, et al.. An advanced video camera system with robust AF, AE, and AWB control[J]. IEEE Transactions on Consumer Electronics, 2001, 47(3):694-699.

LIANG J Y, QIN Y J, HONG Z L. An auto-exposure algorithm for detecting high contrast lighting conditions[C]. 7th International Conference on ASIC. Guilin, P.R.China:IEEE , 2007:725-728.

SHIMIZU S, KONDO T, KOHASHI T, et al.. A new algorithm for exposure control based on fuzzy-logic for video cameras[J]. IEEE Transactions on Consumer Electronics, 1992, 38(3):617-623.

WANG G. Active entropy camera[J]. Machine Vision and Applications, 2012, 23(4):713-723.

LEE C H, HUANG C M, LIOU J Y. Passive automatic exposure mechanism[J]. Optik-International Journal for Light and Electron Optics, 2013, 124(21):4952-4955.

SU Y, LIN J Y, KUO C C J. A model-based approach to camera's auto exposure control[J]. Journal of Visual Communication and Image Representation, 2016, 36:122-129.

KAO W C, HSU C C, KAO C C, et al.. Adaptive exposure control and real-time image fusion for surveillance systems[C].2006 IEEE International Symposium on Circuits and Systems , Island of Kos:IEEE , 2006.

SCHULZ S, GRIMM M, GRIGAT R R. Using brightness histogram to perform optimum auto exposure[J]. WSEAS Transactions on Systems and Control, 2007, 2(2):93-100.

VUONG Q K, YUN S H, KIM S. A new auto exposure system to detect high dynamic range conditions using CMOS technology[C]. Third International Conference on Convergence and Hybrid Information Technology , 2008, ICCIT '08, Busan:IEEE , 2008, 1:577-580.

王晓涛, 王绪安, 康宁. CCD摄像机新型光控技术研究[J].红外与激光工程, 2016, 45(1):120003.

WANG X T, WANG X A, KANG N. New light-control technology research of CCD camera[J]. Infrared and Laser Engineering, 2016, 45(1):120003.(in Chinese)

KAO W C, CHENG L W, CHIEN C Y, et al.. Robust brightness measurement and exposure control in real-time video recording[J]. IEEE Transactions on Instrumentation and Measurement, 2011, 60(4):1206-1216.

GU Q Y, Al N A, AOYAMA T, et al.. A high-frame-rate vision system with automatic exposure control[J]. IEICE Transactions on Information and Systems, 2014, 97(4):936-950.

莫春红, 刘波, 丁璐, 等.一种梯度阈值自动调焦算法[J].红外与激光工程, 2014, 43(1):323-327.

MO CH H, LIU B, DING L, et al.. A gradient threshold auto-focus algorithm[J]. Infrared and Laser Engineering, 2014, 43(1):323-327.(in Chinese)

聂海涛, 龙科慧, 马军, 等.采用改进尺度不变特征变换在多变背景下实现快速目标识别[J].光学精密工程, 2015, 23(8):2349-2356.

NIE H T, LONG K H, MA J, et al.. Fast object recognition under multiple varying background using improved SIFT method[J]. Opt. Precision Eng., 2015, 23(8):2349-2356.(in Chinese)

贾平, 徐宁, 张叶.基于局部特征提取的目标自动识别[J].光学精密工程, 2013, 21(7):1898-1905.

JIA P, XU N, ZHANG Y. Automatic target recognition based on local feature extraction[J]. Opt. Precision Eng., 2013, 21(7):1898-1905.(in Chinese)

纪华, 吴元昊, 孙宏海, 等.结合全局信息的SIFT特征匹配算法[J].光学精密工程, 2009, 17(2):439-444.

JI H, WU Y H, SUN H H, et al.. SIFT feature matching algorithm with global information[J]. Opt. Precision Eng., 2009, 17(2):439-444.(in Chinese)

浏览量

629

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

CCD成像系统中模拟前端设计