[1] 李成吾, 左继成. 国内外PVC管技术现状及发展方向[J]. 当代化工, 2015, 44(4): 711-714.

    Li C W, Zuo J C. Technology status-quo and development direction of PVC pipes[J]. Contemporary Chemical Industry, 2015, 44(4): 711-714.

[2] 卢荣胜, 吴昂, 张腾达, 视觉, 等. 检测技术及其在缺陷检测中的应用综述[J]. 光学学报, 2018, 38(8): 0815002.

    Lu R S, Wu A, Zhang T D, et al. Review on automated optical (visual) inspection and its applications in defect detection[J]. Acta Optica Sinica, 2018, 38(8): 0815002.

[3] 苑玮琦, 李绍丽, 李德健. 基于纹理主、旁瓣特征的雪糕棒裂缝缺陷检测[J]. 仪器仪表学报, 2017, 38(11): 2779-2787.

    Yuan W Q, Li S L, Li D J. Detection of ice cream stick crack defects based on texture mainlobe and sidelobe features[J]. Chinese Journal of Scientific Instrument, 2017, 38(11): 2779-2787.

[4] 李克斌, 余厚云, 周申江. 基于形态学特征的机械零件表面划痕检测[J]. 光学学报, 2018, 38(8): 0815127.

    Li K B, Yu H Y, Zhou S J. Surface scratch detection of mechanical parts based on morphological features[J]. Acta Optica Sinica, 2018, 38(8): 0815127.

[5] Zheng H, Jiang B, Lu H F. An adaptive neural-fuzzy inference system (ANFIS) for detection of bruises on Chinese bayberry (Myrica rubra) based on fractal dimension and RGB intensity color[J]. Journal of Food Engineering, 2011, 104(4): 663-667.

[6] Cohen F S, Fan Z, Attali S. Automated inspection of textile fabrics using textural models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1991, 13(8): 803-808.

[7] Chao S M, Tsai D M. Anisotropic diffusion with generalized diffusion coefficient function for defect detection in low-contrast surface images[J]. Pattern Recognition, 2010, 43(5): 1917-1931.

[8] Tsai D M, Hsieh C Y. Automated surface inspection for directional textures[J]. Image and Vision Computing, 1999, 18(1): 49-62.

[9] Hu G H, Wang Q H. Fabric defect detection via un-decimated wavelet decomposition and Gumbel distribution model[J]. Journal of Engineered Fibers and Fabrics, 2018, 13(1): 15-32.

[10] 王庆香, 李迪, 张舞杰, 等. 软性电路板金面缺陷的无监督检测[J]. 光学精密工程, 2010, 18(4): 981-987.

    Wang Q X, Li D, Zhang W J, et al. Unsupervised defect detection for gold surface of flexible printed board[J]. Optics and Precision Engineering, 2010, 18(4): 981-987.

[11] 王泽润, 方益明, 冯海林, 等. 木材节子缺陷检测与定位方法[J]. 激光与光电子学进展, 2018, 55(5): 051501.

    Wang Z R, Fang Y M, Feng H L, et al. Method for wooden knot detection and localization[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051501.

[12] Jeong Y S, Kim S J, Jeong M K. Automatic identification of defect patterns in semiconductor wafer maps using spatial correlogram and dynamic time warping[J]. IEEE Transactions on Semiconductor Manufacturing, 2008, 21(4): 625-637.

[13] 陈广锋, 管观洋, 魏鑫. 基于机器视觉的冲压件表面缺陷在线检测研究[J]. 激光与光电子学进展, 2018, 55(1): 011501.

    Chen G F, Guan G Y, Wei X. Online stamping parts surface defects detection based on machine vision[J]. Laser & Optoelectronics Progress, 2018, 55(1): 011501.

[14] 马艳. 边缘检测技术在PVC型材产品检测中的应用研究[D]. 杭州: 浙江工业大学, 2004: 19- 27.

    MaY. The application research of PVC product inspection by edge detection[D]. Hangzhou: Zhejiang University of Technology, 2004: 19- 27.

[15] 龙晓薇. 基于图像视觉的PVC表面缺陷检测方法及应用[D]. 长沙: 中南大学, 2007: 9- 19.

    Long XW. PVC surface defect detection method based on image vision and application[D]. Changsha: Central South University, 2007: 9- 19.

[16] 龙晓薇, 阳春华, 龙永红. PVC建材表面缺陷检测系统研究与设计[J]. 计算技术与自动化, 2010, 29(2): 46-50.

    Long X W, Yang C H, Long Y H. Research and design on surface defect detection system for PVC building materials[J]. Computing Technology and Automation, 2010, 29(2): 46-50.

[17] Dehghan Tezerjani A, Mehrandezh M, Paranjape R. Optimal spatial resolution of omnidirectional imaging systems for pipe inspection applications[J]. International Journal of Optomechatronics, 2015, 9(4): 261-294.

[18] Prabuwono AS, SulaimanR, Hamdan AR, et al. Development of intelligent visual inspection system (IVIS) for bottling machine[C]∥TENCON 2006 - 2006 IEEE Region 10 Conference, November 14-17,2006, Hong Kong, China. New York: IEEE, 2006: 343887.

[19] 张铮, 王艳萍, 薛桂香. 数字图像处理与机器视觉: Visual C++与Matlab实现[M]. 2版. 北京: 人民邮电出版社, 2014: 70- 72.

    ZhangZ, Wang YP, Xue GX. Digital image processing and machine vision: implementation of Visual C++ and Matlab[M]. 2nd ed. Beijing: Posts and Telecommunications Press, 2014: 70- 72.

[20] 蒋笑笑, 张振军, 王耀南, 等. 基于灰度投影梯度扩散的PET满瓶快速检测[J]. 电子测量与仪器学报, 2016, 30(8): 1152-1159.

    Jiang X X, Zhang Z J, Wang Y N, et al. PET full bottle fast detection based on gradient diffusion of gray projection[J]. Journal of Electronic Measurement and Instrumentation, 2016, 30(8): 1152-1159.

[21] 高红波, 王卫星. 一种二值图像连通区域标记的新算法[J]. 计算机应用, 2007, 27(11): 2776-2777, 2785.

    Gao H B, Wang W X. New connected component labeling algorithm for binary image[J]. Computer Applications, 2007, 27(11): 2776-2777, 2785.