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Image segmentation and matting based on the extended distance transform

Łagodziński P., Smołka B.

Journal of Medical Informatics & Technologies

2008

Vol. 12

151--156

In this paper we present a novel semi-automatic method for image segmentation and matting that utilizes the newly proposed generalized distance transform to determine the hybrid distance between the foreground and background regions within the image. This distance values are then used to estimate the alpha matting coefficient needed for composing new image by blending the foreground objects into a new background image scene. The effectiveness of the proposed algorithm allows the user to work interactively and to obtain the desired results promptly after marking the regions by scribbling the image. In the paper we show, that the proposed method yields satisfactory results for gray scale and colour images.

Least square image matting

Kun W., Nanning Z., Huilai Q.

Machine Graphics and Vision

2007

Vol. 16, No. 1/2

139-152

This paper addresses the well-known problem of natural image matting. Most of the previous matting algorithms require the user to define the tri-map, which is an inconvenient work and sometimes a burden, especially in a complex situation. This paper uses ceratain user defined foreground and background strokes to estimate the image matte. First we use a Gauss Markov random field to model the matting problem. Then we use the least square optimization approach to solve it. Experimental results show that our approach could properly handle confused boundaries. It also could deal with semi-transparent conditions such as fire etc.