Research on rotary drum assembly and adjustment technology based on improved probabilistic Hough transform

JIANG Junjia;SHEN Jianxin;ZHOU Zhe;HAN Peng

CN Submission Journal Articles Figures Search
Adv. Search

  • Sponsored by:

    Editor-In-Chief:

    ISSN 1002-2082

    　

  • Hosted By:

    Published By: Journal of Applied Optics

    CN 61-1171/O4

Journal of Applied Optics ›› 2020, Vol. 41 ›› Issue (2) : 394-399. DOI: 10.5768/JAO202041.0205003

Research on rotary drum assembly and adjustment technology based on improved probabilistic Hough transform

  • JIANG Junjia1, SHEN Jianxin1, ZHOU Zhe1, HAN Peng1
Author information +
History +

Abstract

In order to solve the problem that when installing the slit lamp in the rotary drum, the human eye has an uncertainty of calculating the center distance of the cross-hair in the drum image, a digital adjustment technique based on the improved probabilistic Hough transform was proposed. By preprocessing the original image, improving the probability Hough line detection, and formulating the line intersection screening rules, the high-precision drum image cross-hair straight line detection and cross-hair center distance calculation were realized. Experiments show that the improved probability Hough transform can accurately detect the crosshairs in the image and fit the excess straight line 100% into 4 straight lines; and the intersection point screening rule can be used to accurately screen out 2 effective intersection points. The adjustment technology can realize digital assembly of rotary drum and the digital information can be used to remind the workers of the adjustment of drums better or, which can meet the actual needs of the drum production line.

Key words

slit lamp drum / probability Hough transform / digital adjustment / line detection / intersection detection

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations
JIANG Junjia, SHEN Jianxin, ZHOU Zhe, HAN Peng. Research on rotary drum assembly and adjustment technology based on improved probabilistic Hough transform. Journal of Applied Optics. 2020, 41(2): 394-399 https://doi.org/10.5768/JAO202041.0205003

References

隋成华, 沃圣杰, 高楠, 等. 数码裂隙灯显微镜光学系统的设计与实现[J]. 光子学报,2017,46(7):179-187.
陈华, 沈建新, 姚凤莹. 基于裂隙灯转鼓的数字化装校技术研究[J]. 应用光学,2019(1):127-131.
王竞雪, 朱庆, 王伟玺, 等. 结合边缘编组的Hough变换直线提取[J]. 遥感学报,2014,18(2):378-389.
刘通, 陈浩, 沈鸣, 等. 随机HOUGH变换提取空间碎片激光测距有效回波[J]. 中国激光,2016,43(4):175-185.
鄢然, 张李超, 张宜生, 等. 基于特征识别的经编布花边实时识别算法[J]. 激光与光电子学进展,2015,52(11):103-107.
巩学美, 高昆, 王研, 等. 一种基于概率Hough变换的遥感图像中线目标检测新方法[J]. 影像科学与光化学,2017,35(2):162-167.
张振杰, 郝向阳, 刘松林, 等. 基于HOUGH一维变换的直线检测算法[J]. 光学学报,2016,36(4):0412005.
段汝娇, 赵伟, 黄松岭, 等. 一种基于改进HOUGH变换的直线快速检测算法[J]
SUI Chenghua, WO Shengjie, GAO Nan, et al. Design and implementation of digital slit-lamp microscope optical system[J]. Acta Photonica Sinca,2017,46(7):179-187.
CHEN Hua, SHEN Jianxin, YAO Fengying. Research on digital alignment technology based on rotating drum of slit-lamp[J]. Journal of Applied Optics,2019(1):127-131.
SHAPIRO S D. Feature space transforms for curve detection[J]. Pattern Recognition,1978,10(3):129-143.
DUDA R O, HART P E. Use of the hough transformation to detect lines and curves in pictures[J]. Communications of the Association for Computing Machinery,1972,15(1):11-15.
HOUGH P V C. A method and means for recognizing complex patterns, US 3069654[P]. U S: Patent3, 1962-03-25.
WANG Jingxue, ZHU Qing, WANG Weixi, et al. Straight line extraction algorithm by Hough transform combining edge grouping[J]. Journal of Remote Sensing,2014,18(2):378-389.
XU L, OJA E, KULTANEN P. A new curve detection method: randomized Hough transform (RHT)[J]. Pattern Recognition Letters,1990,1

9

Accesses

0

Citation

Detail
Sections
Recommended

/

〈 〉