Electrowetting defect image segmentation based on improved Otsu method

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.