资源论文Error-tolerant Scribbles Based Interactive Image Segmentation

Error-tolerant Scribbles Based Interactive Image Segmentation

2019-12-16 | |  141 |   44 |   0

Abstract

Scribbles in scribble-based interactive segmentation such as graph-cut are usually assumed to be perfectly accurate, i.e., foreground scribble pixels will never be segmented as background in the fifinal segmentation. However, it can be hard to draw perfectly accurate scribbles, especially on fifine structures of the image or on mobile touch-screen devices. In this paper, we propose a novel ratio energy function that tolerates errors in the user input while encouraging maximum use of the user input information. More specififically, the ratio energy aims to minimize the graphcut energy while maximizing the user input respected in the segmentation. The ratio energy function can be exactly optimized using an effificient iterated graph cut algorithm. The robustness of the proposed method is validated on the GrabCut dataset using both synthetic scribbles and manual scribbles. The experimental results show that the proposed algorithm is robust to the errors in the user input and preserves the anchoringcapability of the user input.

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