基于改进Otsu的电润湿缺陷图像分割

廖钦楷,林珊玲,林志贤,等. 基于改进Otsu的电润湿缺陷图像分割[J]. 光电工程,2020,47(6):190388. doi: 10.12086/oee.2020.190388
引用本文: 廖钦楷,林珊玲,林志贤,等. 基于改进Otsu的电润湿缺陷图像分割[J]. 光电工程,2020,47(6):190388. doi: 10.12086/oee.2020.190388
Liao Q K, Lin S L, Lin Z X, et al. Electrowetting defect image segmentation based on improved Otsu method[J]. Opto-Electron Eng, 2020, 47(6): 190388. doi: 10.12086/oee.2020.190388
Citation: Liao Q K, Lin S L, Lin Z X, et al. Electrowetting defect image segmentation based on improved Otsu method[J]. Opto-Electron Eng, 2020, 47(6): 190388. doi: 10.12086/oee.2020.190388

基于改进Otsu的电润湿缺陷图像分割

  • 基金项目:
    国家重点研发计划资助项目(2016YFB0401503);福建省科技重大专项资助项目(2014HZ0003-1);广东省科技重大专项资助项目(2016B090906001);广东省光信息材料与技术重点实验室开放基金资助项目(2017B030301007)
详细信息
    作者简介:
    通讯作者: 林志贤(1975-),男,博士,教授,博士生导师,主要从事信息显示技术与平板显示器件驱动方面的研究。E-mail:lzx2005000@163.com
  • 中图分类号: TP391.4

Electrowetting defect image segmentation based on improved Otsu method

  • Fund Project: Supported by National Key Research and Development Program of China (2016YFB0401503), Science and Technology Major Program of Fujian Province (2014HZ0003-1), Science and Technology Major Program of Guangdong Province (2016B090906001) and the Guangdong Provincial Key Laboratory of Optical Information Materials and Technology (2017B030301007)
More Information
  • 针对像素缺陷影响电润湿电子纸的显示效果,本文提出一种基于Otsu的自动阈值检测方法对缺陷进行检测。Otsu是一种常用的自动阈值方法,在图像直方图为双峰时,该方法能给出令人满意的结果。但是电润湿缺陷图像直方图通常为单峰,容易得到错误的结果。电润湿由于不同颜色的填充油墨使得缺陷与背景对比度不同,导致分割更加困难。本文在目标方差前引入加权系数,权值随着缺陷的累积概率的增大而减小。权值在阈值过峰前保持较大的数值,过峰后权值降低,保证了阈值在单峰情况下始终处于峰的左边。实验结果表明:本文提出的方法能够有效分割电润湿缺陷区域,尤其在对比度较低的电润湿缺陷图像中比Otsu、VE、WOV和熵加权方法的ME值更接近0,有更好的分割效果。

  • Overview: Electrowetting is an electronic paper display with the advantages of fast response, low cost, and low energy loss. Electrowetting display technology is currently in a high-speed development period. Electrowetting devices may have defects in the production process, due to ink spillage, the uneven spin coating of the hydrophobic insulating layer, and externally introduced impurities. Defects affect the display of electrowetting devices, so the detection of defects is indispensable. Aiming at the effect of pixel defects on the display of electrowetting electronic paper, an automatic threshold detection method based on Otsu is proposed to detect defects. Otsu is a commonly used automatic threshold method that gives satisfactory results when the image histogram is bimodal. However, since the electrowetting defect image histogram is usually unimodal, it is easy to get incorrect results. Moreover, the electrowetting electronic paper is filled with pixels by three primary inks to realize color display, so the contrast between the defect and the background is different, and the difficulty of segmentation is also different. In order to separate the electrowetting defects in different shades of ink, an improved Otsu threshold segmentation algorithm is proposed. The basic principle of the method is to introduce a weighting factor before the target variance and affect the value of the variance between-class by the weighting factor, which affects the final threshold selection. The weight decreases with the increase of the probability of accumulation of defects, and the weight is always at a higher value when the threshold is at the left edge of the peak. Specifically, the weights have different change rules before and after the peak to change the contribution of the defect variance. When the threshold passes through the peak, the contribution of the defect variance is reduced, and the value of the between-class variance is affected by the weight, which can make the threshold on the left side of the peak. The experimental results show that the proposed method can effectively segment the electrowetting defect area. In the electrowetting defect image in the dark ink with low contrast, the ME value of this method is small. Otsu and other automatic threshold methods have ME values above 0.87, and the segmentation results are far from the desired threshold. The proposed method can segment defects in different inks and have better segmentation effects especially when the contrast of defects and background is low.

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  • 图 1  电润湿显示原理示意图及测试样品。(a)油墨平铺在像素格中;(b)油墨收缩在像素格中;(c)图(a)的测试样品图;(d)图(b)的测试样品图

    Figure 1.  Electrowetting display principle intention and test sample. (a) Ink is tiled in the pixel grid; (b) Ink shrinks in the pixel grid; (c) Test sample diagram of Fig. (a); (d) Test sample diagram of Fig. (b)

    图 2  不同填充油墨中的电润湿器件缺陷。(a)浅色油墨中的电润湿缺陷;(b)深色油墨中的电润湿缺陷

    Figure 2.  Defects of electrowetting devices in different filling inks.(a) Electrowetting defects in light ink; (b) Electrowetting defects in dark ink

    图 3  Otsu缺陷图像分割结果。(a)原始图像;(b) Otsu方法处理结果;(c)直方图和阈值

    Figure 3.  Defect image segmentation result of Otsu method.(a) Original image; (b) Processing result of Otsu; (c) Histogram and threshold values

    图 4  缺陷图像与直方图。(a)原始图像;(b)取不同k值的阈值结果

    Figure 4.  Defect image and histogram. (a) Original image; (b) Thresholding results for different values of k

    图 5  缺陷图像与灰度方差图。(a)原始图像;(b) Otsu结果;(c)本文方法分割结果;(d)灰度方差曲线;(e)灰度方差曲线与加权后缺陷方差曲线;(f) Otsu类间方差曲线与加权后类间方差曲线

    Figure 5.  Defect image and histogram. (a) Original image; (b) Otsu method; (c) Proposed method; (d) Gray variance curve; (e) Gray variance curve and weighted defect variance curve; (f) Between-class variance of Otsu and weighted between-class variance curve

    图 6  五种自动阈值方法对电润湿图像Ⅰ的分割结果。(a)原始图像;(b) VE方法;(c) Otsu方法;(d) WOV方法;(e) EW方法;(f)本文提出方法;(g)直方图和阈值

    Figure 6.  Segmentation results of electrowetting image Ⅰ by five automatic threshold methods. (a) Original image; (b) VE method; (c) Otsu method; (d) WOV method; (e) EW method; (f) Proposed method; (g) Histogram and threshold

    图 7  五种自动阈值方法对电润湿图像Ⅱ的分割结果。(a)原始图像;(b) VE方法;(c) Otsu方法;(d) WOV方法;(e) EW方法;(f)本文提出方法;(g)直方图和阈值

    Figure 7.  Segmentation results of electrowetting image Ⅱ by five automatic threshold methods. (a) Original image; (b) VE method; (c) Otsu method; (d) WOV method; (e) EW method; (f) Proposed method; (g) Histogram and threshold

    图 8  五种自动阈值方法对电润湿图像Ⅲ的分割结果。(a)原始图像;(b) VE方法;(c) Otsu方法;(d) WOV方法;(e) EW方法;(f)本文提出方法;(g)直方图和阈值

    Figure 8.  Segmentation results of electrowetting image Ⅲ by five automatic threshold methods. (a) Original image; (b) VE method; (c) Otsu method; (d) WOV method; (e) EW method; (f) Proposed method; (g) Histogram and threshold

    图 9  五种自动阈值方法对电润湿图像Ⅳ的分割结果。(a)原始图像;(b) VE方法;(c) Otsu方法;(d) WOV方法;(e) EW方法;(f)本文提出方法;(g)直方图和阈值

    Figure 9.  Segmentation results of electrowetting image Ⅳ by five automatic threshold methods. (a) Original image; (b) VE method; (c) Otsu method; (d) WOV method; (e) EW method; (f) Proposed method; (g) Histogram and threshold

    图 10  五种自动阈值方法对电润湿图像Ⅴ的分割结果。(a)原始图像;(b) VE方法;(c) Otsu方法;(d) WOV方法;(e) EW方法;(f)本文提出方法;(g)直方图和阈值

    Figure 10.  Segmentation results of electrowetting image Ⅴ by five automatic threshold methods. (a) Original image; (b) VE method; (c) Otsu method; (d) WOV method; (e) EW method; (f) Proposed method; (g) Histogram and threshold

    表 1  五种方法分割结果的ME值

    Table 1.  ME value of processing result by five methods

    Electrowetting defect image Otsu VE WOV EW Proposed method
    Image Ⅰ 0.0294 0.0289 0.0253 0.8393 0.0239
    Image Ⅱ 0.6663 0.8307 0.0270 0.9677 0.0035
    Image Ⅲ 0.8794 0.8783 0.8830 0.8753 0.0118
    Image Ⅳ 0.8363 0.8363 0.8453 0.8343 0.0465
    Image Ⅴ 0.8547 0.8547 0.8585 0.8542 0.0144
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  • [1]

    Hayes R A, Feenstra B J. Video-speed electronic paper based on electrowetting[J]. Nature, 2003, 425(6956): 383–385. doi: 10.1038/nature01988

    [2]

    Overton G. ELECTRONIC PAPER DISPLAYS: Kindles and cuttlefish: Biomimetics informs e-paper displays[J]. Laser Focus World, 2012, 48(12): 16. http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ0228428854/

    [3]

    Hayes R A, Feenstra B J, Camps I G J, et al. 52.1: a high brightness colour 160 PPI reflective display technology based on electrowetting[J]. SID Symposium Digest of Technical Papers, 2004, 35(1): 1412–1415. doi: 10.1889/1.1825770

    [4]

    Cheng W Y, Lo K L, Chang Y P, et al. 37.1: novel development of large-sized electrowetting display[J]. SID Symposium Digest of Technical Papers, 2008, 39(1): 526–529. doi: 10.1889/1.3069718

    [5]

    Kuo S W, Chang Y P, Cheng W Y, et al. 34.3: novel development of multi-color electrowetting display[J]. SID Symposium Digest of Technical Papers, 2009, 40(1): 483–486. doi: 10.1889/1.3256821

    [6]

    Schultz A, Heikenfeld J, Kang H S, et al. 1000:1 contrast ratio transmissive electrowetting displays[J]. Journal of Display Technology, 2011, 7(11): 583–585. doi: 10.1109/JDT.2011.2160842

    [7]

    Chang R L J, Liu P W, Wu C Y, et al. 54.2: reliable and high performance transparent electrowetting displays[J]. SID Symposium Digest of Technical Papers, 2014, 45(1): 785–788. doi: 10.1002/j.2168-0159.2014.tb00206.x

    [8]

    Zhang X M, Bai P F, Hayes R A, et al. Novel driving methods for manipulating oil motion in electrofluidic display pixels[J]. Journal of Display Technology, 2016, 12(2): 200–205. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=b7cce66d2ef188d3e4d7ea5b51137625

    [9]

    赵瑞, 田志强, 刘启超, 等.介电润湿液体光学棱镜[J].光学学报, 2014, 34(12): 1223003. http://d.old.wanfangdata.com.cn/Periodical/hbydjs201205003

    Zhao R, Tian Z Q, Liu Q C, et al. Electrowetting-based liquid prism[J]. Acta Optica Sinica, 2014, 34(12): 1223003. http://d.old.wanfangdata.com.cn/Periodical/hbydjs201205003

    [10]

    钱明勇, 林珊玲, 曾素云, 等.电润湿电子纸的实时动态显示驱动系统实现[J].光电工程, 2019, 46(6): 180623. doi: 10.12086/oee.2019.180623

    Qian M Y, Lin S L, Zeng S Y, et al. Real-time dynamic driving system implementation of electrowetting display[J]. Opto-Electronic Engineering, 2019, 46(6): 180623. doi: 10.12086/oee.2019.180623

    [11]

    Jin S Q, Ji C, Yan C C, et al. TFT-LCD mura defect detection using DCT and the dual-γ piecewise exponential transform[J]. Precision Engineering, 2018, 54: 371–378. doi: 10.1016/j.precisioneng.2018.07.006

    [12]

    何俊杰, 肖可, 刘畅, 等.基于区域神经网络的TFT-LCD电路缺陷检测方法[J].计算机与现代化, 2018(7): 33–38. doi: 10.3969/j.issn.1006-2475.2018.07.007

    He J J, Xiao K, Liu C, et al. TFT-LCD circuit defects detection based on faster R-CNN[J]. Computer and Modernization, 2018(7): 33–38. doi: 10.3969/j.issn.1006-2475.2018.07.007

    [13]

    Otsu N. A threshold selection method from gray-level histograms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 1979, 9(1): 62–66. doi: 10.1109/TSMC.1979.4310076

    [14]

    Ng H F. Automatic thresholding for defect detection[J]. Pattern Recognition Letters, 2006, 27(14): 1644–1649. doi: 10.1016/j.patrec.2006.03.009

    [15]

    Fan J L, Lei B. A modified valley-emphasis method for automatic thresholding[J]. Pattern Recognition Letters, 2012, 33(6): 703–708. doi: 10.1016/j.patrec.2011.12.009

    [16]

    张博, 倪开灶, 王林军, 等.基于背景校正和图像分割定量分析光学元件表面疵病的新算法[J].光学学报, 2016, 36(9): 0911004. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxxb201609015

    Zhang B, Ni K Z, Wang L J, et al. New algorithm of detecting optical surface imperfection based on background correction and image segmentation[J]. Acta Optica Sinica, 2016, 36(9): 0911004. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=gxxb201609015

    [17]

    Yuan X C, Lu W S, Peng Q J. An improved Otsu method using the weighted object variance for defect detection[J]. Applied Surface Science, 2015, 349: 472–484. doi: 10.1016/j.apsusc.2015.05.033

    [18]

    Truong M T N, Kim S. Automatic image thresholding using Otsu's method and entropy weighting scheme for surface defect detection[J]. Soft Computing, 2018, 22(13): 4197–4203. doi: 10.1007/s00500-017-2709-1

    [19]

    Liao P S, Chen T S, Chung P C. A fast algorithm for multilevel thresholding[J]. Journal of Information Science and Engineering, 2001, 17(5): 713–727. http://d.old.wanfangdata.com.cn/OAPaper/oai_arXiv.org_cs%2f0602044

    [20]

    Yasnoff W A, Mui J K, Bacus J W. Error measures for scene segmentation[J]. Pattern Recognition, 1977, 9(4): 217–231. doi: 10.1016/0031-3203(77)90006-1

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出版历程
收稿日期:  2019-07-06
修回日期:  2019-11-08
刊出日期:  2020-06-01

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