High dynamic stripe image enhancement for reliable center extraction in complex environment

被引:3
作者
Pan, Xiao [1 ]
Liu, Zhen [1 ]
机构
[1] Beihang Univ, Minist Educ, Key Lab Precis Optomechatron Technol, Beijing, Peoples R China
来源
PROCEEDINGS OF 2017 INTERNATIONAL CONFERENCE ON VIDEO AND IMAGE PROCESSING (ICVIP 2017) | 2017年
关键词
High dynamic; Retinex theroy; Reflectivity; Enhancemnet;
D O I
10.1145/3177404.3177406
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
High-precision laser vision sensors, as an important mean of 3D data acquisition, are being widely used for online high-speed measurement in complex environment. However, due to the complexity of the scene environment, the stripe images show high dynamic, low signal to noise ratio, which seriously affect the reliability and detection accuracy. In this paper, a high dynamic stripe image brightness enhancement method is proposed. The Retinex theory is adopted to enhance stripe brightness, which makes the gray value of stripe in cross-section is close to Gaussian distribution. Meanwhile, the stripe is segmented correctly based on the reflectivity, which ensures low quality stripes can be enhanced correctly. In that case, the central coordinate of stripe can be easily extracted. Finally, a multi-thread flow acceleration and serialized output program are used to meet the requirement of real-time measurement. The physical experiments indicate that this method can improve the system reliability greatly, which has important practical application value.
引用
收藏
页码:135 / 139
页数:5
相关论文
共 9 条
[1]  
[Anonymous], 1997, MULTISCALE RETINEX B
[2]   Blind inverse gamma correction [J].
Farid, H .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2001, 10 (10) :1428-1433
[3]  
Jin Y, 2001, INT SOC OPTICS PHOTO
[4]   Properties and performance of a center/surround retinex [J].
Jobson, DJ ;
Rahman, ZU ;
Woodell, GA .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1997, 6 (03) :451-462
[5]   RECENT ADVANCES IN RETINEX THEORY AND SOME IMPLICATIONS FOR CORTICAL COMPUTATIONS - COLOR-VISION AND THE NATURAL IMAGE [J].
LAND, EH .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-PHYSICAL SCIENCES, 1983, 80 (16) :5163-5169
[6]   Finding a small number of regions in an image using low-level features [J].
Lau, HF ;
Levine, MD .
PATTERN RECOGNITION, 2002, 35 (11) :2323-2339
[7]  
Lucchese L., 2001, ENG COMPUT, V12, P1
[8]   An unbiased detector of curvilinear structures [J].
Steger, C .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1998, 20 (02) :113-125
[9]  
Subr K, 2005, LECT NOTES COMPUT SC, V3617, P171, DOI 10.1007/11553595_21