Electrowetting defect image segmentation based on improved Otsu method

Liao Qinkai; Lin Shanling; Lin Zhixian; Chen Zheliang; Li Tiantian; Tang Biao

doi:10.12086/oee.2020.190388

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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

Electrowetting defect image segmentation based on improved Otsu method

1.
Institute of Optlelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou, Fujian 350116, China
2.
College of Physics and Information Engineering, Fuzhou University, Fuzhou, Fujian 350116, China
3.
Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, Guangdong 510006, China

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

Corresponding author: Lin Zhixian,E-mail：lzx2005000@163.com

Received Date 06 July 2019

Revised Date 08 November 2019

Published Date 01 June 2020

Abstract

Abstract

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, the electrowetting defect image histogram is usually a single peak, and Otsu method fails. Electrowetting differs from the background contrast due to the filling inks of different colors, making segmentation more difficult. In this paper, the weighting coefficient is introduced before the target variance, and the weight decreases as the cumulative probability of defects increases. The weight keeps a large value before the threshold crosses the peak, and the weight decreases after the peak, ensuring that the threshold is always to the left of the peak in the case of a single peak. The experimental results show that the proposed method can effectively segment the electrowetting defect region, especially in the electrowetting defect image with lower contrast ratio. The method is closer to 0 compared to the ME value of Otsu, VE, WOV and entropy weighting methods. The proposed method has a better segmentation effect.
- electrowetting display /
- image processing /
- machine vision /
- defect segmentation /
- Otsu method

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References

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Overview

Overview

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.