[1] 胡方尚. 印刷质量的图像检测技术研究［D］. 上海: 华东理工大学, 2017

    HU Fangshang. Research on image detection technology of printing quality［D］. Shanghai: East China University of Science and Technology, 2017.

[2] 王凡, 倪晋平, 董涛, 等. 结合视觉注意力机制和图像锐度的无参图像质量评价方法［J］. 应用光学, 2018, 39(1): 51-56.

    WANG Fan, NI Jinping, DONG Tao, et al. No-reference image quality assessmentmethodbasedon visual attention mechanism and sharpness metric approach［J］. Journal of Applied Optics, 2018, 39(1): 51-56.

[3] BAE S H, KIM M. A novel image quality assessment with globally and locally consilient visual quality perception［J］. IEEE Transactions on Image Processing, 2016, 25(5): 2392-2406.

[4] JI L P, REN Y, LIU G S, et al. Training-based gradient LBP feature models for multiresolution texture classification［J］. IEEE Transactions on Cybernetics, 2018, 48(9): 2683-2696.

[5] 蔡川丽, 张建平, 张彦博, 等. 一种抗姿态与表情变化的三维人脸识别方法［J］. 应用光学, 2018, 39(4): 491-499.

    CAI Chuanli, ZHANG Jianping, ZHANG Yanbo, et al. 3D face recognition method against gesture and expression change［J］. Journal of Applied Optics, 2018, 39(4): 491-499.

[6] 孙晓娜, 刘继超, 高国华, 等. 基于视觉的乳品包装日期喷码缺陷检测技术［J］. 食品与机械, 2018, 34(10): 100-103,108.

    SUN Xiaona, LIU Jichao, GAO Guohua, et al. Study on visual code-based defect detection technology for production date of dairy packaging［J］. Food & Machinery, 2018, 34(10): 100-103,108.

[7] 杜宇. 基于机器视觉的药品包装检测系统研究与设计［D］. 天津：天津大学, 2018.

    DU Yu.Research and design of medicine packaging detection system based on machine vision［D］.Tianjin:Tianjin University,2018.

[8] 亢宇欣, 谌贵辉, 张三炳, 等. 基于Halcon的贴片电阻方向检测系统［J］. 包装工程, 2017, 38(23):116-120.

    KANG Yuxin, CHEN Guihui, ZHANG Sanbing, et al. Chip resistance direction detection system based on halcon［J］. Packaging Engineering, 2017, 38(23): 116-120.

[9] 汪清芳. 基于机器视觉的标签缺陷检测系统设计与实现［D］. 成都: 电子科技大学, 2014.

    WANG Qingfang. Design and implementation of label detection system based on machine vision［D］. Chengdu: University of Electric Science and Technology of China, 2014.

[10] 田旭. 基于机器视觉的电子标签表面质量检测系统设计［D］. 杭州: 浙江工业大学, 2014.

    TIAN Xu. The design of electronic tags surface quality inspection system based on machine vision［D］. Hangzhou: Zhejiang University of Technology, 2014.

[11] GALBALLY J , MARCEL S, FIéRREZ J. Image quality assessment for fake biometric detection: application to iris, fingerprint, and face recognition［J］. IEEE Transactions on Image Process, 2014, 23(2):710-724.

[12] ZHANG L, ZHANG L, MOU X Q, et al. FSIM: A feature similarity index for image quality assessment［J］. IEEE Transactions on Image Processing, 2011, 20(8): 2378-2386.

[13] 刘国军, 高丽霞, 陈丽奇, 等. 广义平均的全参考型图像质量评价池化策略［J］. 光学精密工程, 2017, 25(3): 742-748.

    LIU Guojun, GAO Lixia, CHEN Liqi, et al. Pooling strategy for full-reference IQA via general means［J］. Optics and Precision Engineering, 2017, 25(3): 742-748.

[14] 高攀. 基于改进LBP算子的图像纹理分类研究［D］. 成都: 西南交通大学, 2018.

    GAO Pan. Research on image texture classification based on improved LBP operator［D］. Chengdu: Southwest Jiaotong University, 2018.

[15] OJALA T, PIETIKAINEN M, MAENPAA T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24(7): 971-987.

[16] 梁志虎, 张小宁, 岳俊峰, 等. 基于双线性插值最值滤波的Mura改善方法［J］. 光子学报, 2016, 45(7): 30-35.

    LIANG Zhihu, ZHANG Xiaoning, YUE Junfeng, et al. Improvement of Mura based on the maximum/minimum bilinear interpolation method［J］. Acta Photonica Sinica, 2016, 45(7): 30-35.