• Laser & Optoelectronics Progress
  • Vol. 56, Issue 5, 051001 (2019)
Chao Xu* and Xueliang Ping
Author Affiliations
  • Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
  • show less
    DOI: 10.3788/LOP56.051001 Cite this Article Set citation alerts
    Chao Xu, Xueliang Ping. Line Detection Algorithm Based on Improved Random Hough Transformation[J]. Laser & Optoelectronics Progress, 2019, 56(5): 051001 Copy Citation Text show less
    References

    [1] Nie H T, Long K H, Ma J et al. Fast object recognition under multiple varying background using improved SIFT method[J]. Optics and Precision Engineering, 23, 2349-2356(2015).

    [2] Ulrich M, Wiedemann C, Steger C. Combiningscale-space and similarity-based aspect graphs for fast 3D object recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34, 1902-1914(2012). http://dl.acm.org/citation.cfm?id=2361198

    [3] Piella G. Heijmans H J A M. Adaptive lifting schemes with perfect reconstruction[J]. IEEE Transactions on Signal Processing, 50, 1620-1630(2002).

    [4] Hua C J, Xiong X M, Chen Y. Feature extraction of workpiece circular arc contour based on Sobel operator[J]. Laser & Optoelectronics Progress, 55, 021011(2018).

    [5] Wang L, Liu Q. A multi-object image segmentation algorithm based on local features[J]. Laser & Optoelectronics Progress, 55, 061002(2018).

    [6] Wang W X, Fu Y T, Dong F et al. Infrared ship target detection method based on deep convolution neural network[J]. Acta Optica Sinica, 38, 0712006(2018).

    [8] Xu L, Oja E, Kultanen P. A new curve detection method: randomized Hough transform (RHT)[J]. Pattern Recognition Letters, 11, 331-338(1990). http://www.sciencedirect.com/science/article/pii/016786559090042Z?via=ihub&cc=y

    [9] Matas J, Galambos C, Kittler J. Robust detection of lines using the progressive probabilistic Hough transform[J]. Computer Vision and Image Understanding, 78, 119-137(2000). http://www.sciencedirect.com/science/article/pii/S1077314299908317

    [10] Zhang Z J, Hao X Y, Liu S L et al. Line detection based on Hough one-dimensional transform[J]. Acta Optica Sinica, 36, 0412005(2016).

    [11] Ji J H, Chen G D, Sun L N. A novel Hough transform method for line detection by enhancing accumulator array[J]. Pattern Recognition Letters, 32, 1503-1510(2011). http://www.sciencedirect.com/science/article/pii/S0167865511001115

    [12] Diao Y, Wu C K, Luo H et al. A line detection optimization algorithm based on improved probabilistic Hough transform[J]. Acta Optica Sinica, 38, 0815016(2018).

    [13] Sun J F, Ding S W, Zhang X H et al. Linear feature detection algorithm combined with pixel local contrast[J]. Journal of National University of Defense Technology, 39, 31-38(2017).

    [14] Zhang J X, Shen X L, Wang H et al. Fast multi-line detection algorithm using randomized Hough transform[J]. Journal of Zhejiang University of Technology, 41, 346-350(2013).

    [15] Wang J X, Zhu Q, Wang W X et al. Straight line extraction algorithm by Hough transform combining edge grouping[J]. Journal of Remote Sensing, 18, 378-389(2014).

    [16] Zhen Y, Liu X J, Wang M Z. An improved RANSAC of fundamental matrix estimation method[J]. Bulletin of Surveying and Mapping, 4, 39-43(2014).

    Chao Xu, Xueliang Ping. Line Detection Algorithm Based on Improved Random Hough Transformation[J]. Laser & Optoelectronics Progress, 2019, 56(5): 051001
    Download Citation