Evaluating the robustness of image matting algorithm. Issue 4 (17th July 2020)

• Record Type: Journal Article
• Authors: Yuan, Genji; Li, Jinjiang; Fan, Hui
• Is Part Of: CAAI transactions on intelligence technology. Volume 5:Issue 4(2020)
• Page Start: 247
• Page End: 259
• Publication Date: 2020-07-17
• Subjects: feature extraction -- Gaussian processes -- image texture -- image denoising -- image restoration; image matting algorithm -- alpha masking -- consistent alpha masks -- Gaussian–Hermite moment -- gradient amplitude -- gradient direction -- texture changes -- Gaussian blur -- pretzel noise -- noise alpha mask -- evaluation levels -- noise level -- noisy images -- trap matting algorithm; Artificial intelligence -- Periodicals; Computer science -- Periodicals; Artificial intelligence; Computer science; Electronic journals; Periodicals; 006.305
• DOI: 10.1049/trit.2020.0079
• Languages: English
• ISSNs: 2468-6557

Abstract

Abstract : In this study, the authors propose a method to calculate the consistency of alpha masking to assess the robustness of the matting algorithm. This study evaluates consistent alpha masks based on the Gaussian–Hermite moment in combination with gradient amplitude and gradient direction. The gradient direction describes the appearance and shape of local objects in the image, and the gradient amplitude accurately reflects the contrast and texture changes of small details in the image. They selected Gaussian blur, pretzel noise, and combined noise to destroy the image, and then evaluated the consistency of the original alpha mask and noise alpha mask. To determine the robustness of the matting algorithm, they assessed the degree of consistency of the alpha mask using three different evaluation levels. The experimental results show that noise has a greater impact on the performance of the matting algorithm, which shows a decreasing trend as the noise level in the image deepens. In noisy images, the traditional matting algorithm exhibits better robustness compared to the recently proposed trap matting algorithm. Different matting algorithms present different adaptations to different noises.