An automatic and efficient foreground object extraction scheme
This addresses the problem of automated object extraction for image processing applications, but it appears incremental as it builds on standard techniques like Canny edge detection without novel breakthroughs.
The paper tackles foreground object extraction from color images by converting to grayscale, applying Canny edge detection, and filling bounded regions, resulting in a color image containing only the foreground object.
This paper presents a method to differentiate the foreground objects from the background of a color image. Firstly a color image of any size is input for processing. The algorithm converts it to a grayscale image. Next we apply canny edge detector to find the boundary of the foreground object. We concentrate to find the maximum distance between each boundary pixel column wise and row wise and we fill the region that is bound by the edges. Thus we are able to extract the grayscale values of pixels that are in the bounded region and convert the grayscale image back to original color image containing only the foreground object.