Inspection of Slight Aesthetic Defects in a Polarizing Film via Polarization Imaging

HUANG Guangjun; LIE Zhihao; WANG Xingzheng; ZHONG Xiaopin; DENG Yuanlong

doi:10.11999/JEIT210870

Volume 44 Issue 5

May 2022

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(5): 1636-1642

HUANG Guangjun, LIE Zhihao, WANG Xingzheng, ZHONG Xiaopin, DENG Yuanlong. Inspection of Slight Aesthetic Defects in a Polarizing Film via Polarization Imaging[J]. Journal of Electronics & Information Technology, 2022, 44(5): 1636-1642. doi: 10.11999/JEIT210870

Citation:

HUANG Guangjun, LIE Zhihao, WANG Xingzheng, ZHONG Xiaopin, DENG Yuanlong. Inspection of Slight Aesthetic Defects in a Polarizing Film via Polarization Imaging[J]. Journal of Electronics & Information Technology, 2022, 44(5): 1636-1642. doi: 10.11999/JEIT210870

Citation:

PDF( 2733 KB)

Inspection of Slight Aesthetic Defects in a Polarizing Film via Polarization Imaging

doi: 10.11999/JEIT210870

College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China

Funds: The National Natural Science Foundation of China (62171288), Shenzhen Basic Research Project (20190808143415801, 20180305123922293)

Received Date: 2021-08-24
Rev Recd Date: 2021-11-01

Available Online: 2021-11-13

Publish Date: 2022-05-25

Abstract

Abstract

The slight aesthetic defects of polarizing films can hardly image and are difficult to detect. A novel method of detecting the slight defects based on polarization imaging is proposed in this paper. The mechanism of contrast enhancement is described qualitatively through the measurement results of defect polarization index. The image contrast of the defect is greatly improved by making use of the significant difference of polarization state of the transmitted light between the defect and the normal region, so as to simplify the following image processing algorithm and improve both the detection speed and accuracy. The experimental results show that the average recognition rate of polarizer aesthetic defects is 97.3%, and the average detection time of a single defect sample is about 0.22 s, thus it meets basically the requirements of industrial application.
- Visual detection,
- Defect detection,
- Polarization imaging,
- Polarizing film,
- Principal component Analysis

FullText(HTML)

References(16)

References

[1]	YOON Y G, LEE S L, CHUNG C W, et al. An effective defect inspection system for polarized film images using image segmentation and template matching techniques[J]. Computers & Industrial Engineering, 2008, 55(3): 567–583. doi: 10.1016/j.cie.2008.01.015
[2]	KUO C C F J, CHIU C H, and CHOU Y C. Research and development of intelligent on-line real-time defect inspection system for polymer polarizer[J]. Polymer-Plastics Technology and Engineering, 2009, 48(2): 185–192. doi: 10.1080/03602550802634501
[3]	CHENG C C and JAO H M. Application of the Haar wavelet to Mura detection for polarizer[C]. 2013 IEEE International Conference on Industrial Technology (ICIT), Cape Town, South Africa, 2013: 1080–1085.
[4]	YEN H N and SYU M J. Inspection of polarizer tiny bump defects using computer vision[C]. 2015 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, USA, 2015: 525–527.
[5]	WON Y, JOO H, and KIM J. Classification of defects in the polarizer of display panels using the Convolution Neural Network (CNN)[J]. International Journal of Computing, Communications and Instrumentation Engineering (IJCCIE), 2017, 4(1): 139–142. doi: 10.15242/IJCCIE.E0217018.
[6]	KUO C F J, LAI Chunyu, KAO C H, et al. Integrating image processing and classification technology into automated polarizing film defect inspection[J]. Optics and Lasers in Engineering, 2018, 104: 204–219. doi: 10.1016/j.optlaseng.2017.09.017
[7]	LEI Haiwei, WANG Bin, WU Hehe, et al. Defect detection for polymeric polarizer based on faster R-CNN[J]. Journal of Information Hiding and Multimedia Signal Processing, 2018, 9(6): 1414–1420. doi: 10.15242/ijccie.e0217018
[8]	LIU Ruizhen, SUN Zhiyi, WANG Anhong, et al. Lightweight efficient network for defect classification of polarizers[J]. Concurrency and Computation:Practice and Experience, 2020, 32(11): e5663. doi: 10.1002/cpe.5663
[9]	LAI Wenwei, ZENG Xiaoxing, HE Jian, et al. Aesthetic defect characterization of a polymeric polarizer via structured light illumination[J]. Polymer Testing, 2016, 53: 51–57. doi: 10.1016/j.polymertesting.2016.05.011
[10]	DENG Yuanlong, XU Shaopeng, CHEN Haoquan, et al. Inspection of extremely slight aesthetic defects in a polymeric polarizer using the edge of light between black and white stripes[J]. Polymer Testing, 2018, 65: 169–175. doi: 10.1016/j.polymertesting.2017.11.019
[11]	熊志航, 廖然, 曾亚光, 等. 利用偏振成像在复杂现场快速识别金属碎屑[J]. 红外与激光工程, 2020, 49(6): 10–15. doi: 10.3788/IRLA20201012 XIONG Zhihang, LIAO Ran, ZENG Yaguang, et al. Rapid identification of metal debris in complicated scenes by using polarization imaging[J]. Infrared and Laser Engineering, 2020, 49(6): 10–15. doi: 10.3788/IRLA20201012
[12]	李嘉晋, 廖然, 卓泽鹏, 等. 利用偏振光散射技术的藻类絮凝过程监测[J]. 大气与环境光学学报, 2020, 15(1): 72–80. doi: 10.3969/J.issn.1673-6141.2020.01.008 LI Jiajin, LIAO Ran, ZHUO Zepeng, et al. Monitoring of algal flocculation using polarized light scattering[J]. Journal of Atmospheric and Environmental Optics, 2020, 15(1): 72–80. doi: 10.3969/J.issn.1673-6141.2020.01.008
[13]	FECHNER G T, HOWES D H, and BORING E G. Elements of Psychophysics[M]. New York: Holt, Rinehart and Winston, 1966. doi: 10.1037/11304–026.
[14]	罗勇江, 杨腾飞, 赵冬. 色噪声下基于白化频谱重排鲁棒主成分分析的语音增强算法[J]. 电子与信息学报, 2021, 43(12): 3671–3679. doi: 10.11999/JEI200594 LUO Yongjiang, YANG Tengfei, and ZHAO Dong. Speech enhancement algorithm based on robust principal component analysis with whitened spectrogram rearrangement in colored noise[J]. Journal of Electronics and Information Technology, 2021, 43(12): 3671–3679. doi: 10.11999/JEI200594
[15]	杨依忠, 汪鹏飞, 胡雄楼, 等. 基于鲁棒主成分分析的运动目标检测优化算法[J]. 电子与信息学报, 2018, 40(6): 1309–1315. doi: 10.11999/JEIT170789 YANG Yizhong, WANG Pengfei, HU Xionglou, et al. Moving object detection optimization algorithm based on robust principal component analysis[J]. Journal of Electronics &Information Technology, 2018, 40(6): 1309–1315. doi: 10.11999/JEIT170789
[16]	CHIPMAN R A, LAM W S T, and YOUNG G. Polarized Light and Optical Systems[M]. New York: CRC Press, 2018: 66–68.