Threshold-Based Fuzzy C-Means on Closed-Form Solution For Alpha Matting
Segmentation techniques applied, based on matte calculations are named as alpha matting. It is the combination of convex of two colors which provide transparency effects in computer graphics, to distinguish the pixels whether it is whether it is foreground or background, while on the segmentation process, it is focused on the separation of pixels. By defining the threshold value, it defines the unknown region. In general, threshold is based on the user's perception by considering the characteristics of the image extracted, so they need a certain skill in determining threshold to get best matte. User error in determining threshold will affect the quality of matte. In order to solve this problem, an adaptive threshold-based algorithm is proposed to determine the threshold value adaptively, referring to the image characteristics applied as the alpha threshold. In this study, the value of alpha is generated adaptively to improve the matte quality. Adaptable threshold Otsu and Fuzzy C-Means (FCM) algorithms are applied and the results are evaluated to determine the best threshold. Tests performed with the Otsu and FCM algorithms show that the threshold in the FCM algorithm has an accuracy since the matte color distribution in the unknown region is better than the Otsu or Closed-form solution applied in a complex, uniform color. In addition, when the extraction results are compared to ground truth (matte extracted manual), the FCM threshold can reduce the error by 11.05% compared to the Closed-form solution, while Otsu reduce the error by 4.72%.
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