Abstract：Ellipse Hough transform method is a significant research topic in the field of feature extraction. Efficient Hough transform (EHT) is proposed to improve the algorithm's accuracy and timeliness. This method is suitable for detecting the ellipse contour in cylindrical feature. The algorithm mainly consists of estimating other parameters' approximation by single parameter's approximation. EHT's failure model is proposed to give the security error range of preset parameter. Synthetic images of ellipse contour are tested to demonstrate EHT's effectiveness.
 Hough P V. A method and means for recognizing complex patterns: USA, 3069654 [P]. 1962.
 LU Wei, TAN Jinglu. Detection of incomplete ellipse in images with strong noise by iterative randomized Hough transform (IRHT) [J]. Pattern Recognition, 2008, 41(4): 1268-1279.
 Nair P S, Saunders A T. Hough transform based ellipse detection algorithm [J]. Pattern Recognition Letters, 1996, 17(7): 777-784.
 Mclaughlin R A. Randomized Hough transform: Improved ellipse detection with comparison [J]. Pattern Recognition Letters, 1998, 19(3-4): 299-305.
 Chia A Y S, Leung M K H, How-Lung E, et al. Ellipse detection with Hough transform in one dimensional parametric space [C]// ICIP 2007. IEEE International Conference on. San Antonio, TX, USA: IEEE, 2007: 333-336.
 XIE Yonghong, JI Qiang. A new efficient ellipse detection method [C]// Pattern Recognition, 2002. Proceedings. 16th International Conference on. Quebec, Canada: IEEE, 2002: 957-960.
 CHENG Zhiguo, LIU Yuncai. Efficient technique for ellipse detection using restricted randomized Hough transform [C]// Information Technology: Coding and Computing, 2004. Proceedings. International Conference on. Las Vegas, Nevada, USA: IEEE, 2004: 714-718.
 Chien C F, Cheng Y C, Lin T T. Robust ellipse detection based on hierarchical image pyramid and Hough transform [J]. J Opt Soc Am A Opt Image Sci Vis, 2011, 28(4): 581-589.
 HAN Fei, GUO Yanling, WANG Lili. A new ellipse detector based on Hough transform [C]// Information and Computing Science, 2009. Second International Conference on. Manchester: IEEE, 2009: 301-305.
 HE Kaiming, SUN Jian, TANG Xiaoou. Single image haze removal using dark channel prior [J]. Pattern Analysis and Machine Intelligence, 2011, 33(12): 2341-2353.
 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]. 仪器仪表学报, 2010(12): 2774-2780. DUAN Rujiao, ZHAO Wei, HUANG Songling, et al. Fast line detection algorithm based on improved Hough transformation [J]. Chinese Journal of Scientific Instrument, 2010(12): 2774-2780. (in Chinese)
 Park S G, Kim S Y, Kim J Y, et al. Finding the information of the ellipse from the optical Hough transform [C]// International Society for Optics and Photonics. Orlando, Florida: AeroSense, 2000: 352-363.
 杨全银. 基于Hough变换的图像形状特征检测[D]. 山东大学, 2009.YANG Quanyin. Shape features detection based on Hough transform [D]. Shandong: Shandong University, 2009. (in Chinese)