DocumentCode :
3279621
Title :
KNN-based color line model for image matting
Author :
Meiguang Jin ; Byoung-Kwang Kim ; Woo-Jin Song
Author_Institution :
Dept. of Electr. Eng., Pohang Univ. of Sci. & Technol., Pohang, South Korea
fYear :
2013
fDate :
15-18 Sept. 2013
Firstpage :
2480
Lastpage :
2483
Abstract :
Image matting is the extraction of a foreground object from an image and determination of the transparency of each pixel. Matting is inherently an ill-posed and underconstrained problem. Therefore, some assumptions need to be made to solve it. Recent methods that provide a closed-form solution to this problem are based on the assumption of either local smoothness or the nonlocal principle, but they cannot always produce satisfactory matting results. In this paper, we propose a K-nearest neighbors (KNN)-based color line model that combines and preserves the advantages of both the above assumptions. The experimental matting results indicate that they are of comparable or higher quality than those obtained by the existing methods based on the above two assumptions.
Keywords :
feature extraction; image colour analysis; KNN-based color line model; foreground object extraction; image matting; k-nearest neighbor-based color line model; local smoothness; nonlocal principle; pixel transparency determination; alpha mattes; local smoothness; nonlocal principle;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
Type :
conf
DOI :
10.1109/ICIP.2013.6738511
Filename :
6738511
Link To Document :
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