کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
528630 869592 2013 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Using texture to complement color in image matting
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Using texture to complement color in image matting
چکیده انگلیسی


• The texture information is leveraged to complement color in image matting.
• The proposed method combines color and texture information in matting process.
• The proposed combined method presents the best among current matting methods.
• The proposed method has first ranks with respect to MSE and Gradient error.
• Several experiments are carried out to reveal potential power of texture in matting.

Current image matting methods based on color sampling use color to distinguish between foreground and background pixels. However, they fail when the corresponding color distributions overlap. Other methods that define correlation between neighboring pixels based on color aim to propagate the opacity parameter α from known pixels to unknown pixels. However, strong edges of textured regions may block the propagation of α. In this paper, a new matting strategy is proposed that delivers an accurate matte by considering texture as a feature that can complement color even if the foreground and background color distributions overlap and the image is a complex one with highly textured regions. The texture feature is extracted in such a way as to increase distinction between foreground and background regions. An objective function containing color and texture components is optimized to find the best foreground and background pair among a set of candidate pairs. The effectiveness of proposed method is compared quantitatively as well as qualitatively with other matting methods by evaluating their results on a benchmark dataset and a set of complex images. The evaluations show that the proposed method presented the best among state of the art matting methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Image and Vision Computing - Volume 31, Issue 9, September 2013, Pages 658–672
نویسندگان
, ,