Many factors such as production methods and structural parameters have distinctive influence on the quality and performance of a hand woven carpet. To investigate the effects of some variables, eighteen samples of carpet vary, in knot density, pile height and percentage of slipe wool, were manufactured. Pile yarn performance was assessed by using load-displacement compression curve, obtained fr...

Image matting is a technique used to extract a foreground object from an input color image by estimating its opacity mask, which is called an alpha matte. Many previous methods have estimated a poor-quality alpha matte when a foreground object and its background have similar colors. To overcome this problem, we treat an image matting problem as a binary classification problem to classify unknow...

Digital matting consists in extracting a foreground element from a background image. Besides the image, usual matting methods need to be initialized with two disjoint regions : the set of foreground only pixels and the set of background only pixels. Pixels belonging to none of these two regions are considered as an undetermined blending between the foreground and the background. Here, one has t...

While current matting algorithms work very well for some natural images, their performance is questionable in the presence of sharp discontinuities in the foreground and background regions. To counter the above problem, we propose to use variational PDE based inpainting techniques within the matting problem, that are largely successful in inpainting geometric features into unknown regions.

Image matting is the process of computing an alpha value for each pixel that corresponds to the amount of the pixel that is foreground and the amount that is background. This is often used to isolate the foreground and replace the background with a different image. Typically this is done using a special studio and a blue (or green) screen for easier segmentation. However, this method is not as ...

We propose a foreground segmentation algorithm that does foreground extraction under different scales and refines the result by matting. First, the input image is filtered and resampled to 5 different resolutions. Then each of them is segmented by adaptive figure-ground classification and the best segmentation is automatically selected by an evaluation score that maximizes the difference betwee...

Accurately extracting foreground objects is the problem of isolating the foreground in images and video, called image matting which has wide applications in digital photography. This problem is severely ill-posed in the sense that, at each pixel, one must estimate the foreground and background pixels and the so-called alpha value from only pixel information. The most recent work in natural imag...

In computer vision, matting is the process of extracting foreground objects while preserving their pixel-wise coverage in the scene. This coverage is referred to as opacity or alpha matte. Once an accurate alpha matte is estimated, a foreground object can be seamlessly composited onto a new background. In this paper we present a novel patch based non-parametric approach for video matting. The t...