A Modified Mean Shift Algorithm For Efficient Document Image Restoration

Previous formulations of the global Mean Shift clustering algorithm incorporate a global mode finding which requires a lot of computations making it extremely time-consuming. This paper focuses on reducing the computational cost in order to process large document images. We introduce thus a local-global Mean Shift based color image segmentation approach. It is a two-steps procedure carried out by updating and propagating cluster parameters using the mode seeking property of the global Mean Shift procedure. The first step consists in shifting each pixel in the image according to its R-Nearest Neighbor Colors(R-NCC) in the spatial domain. The second step process shifts only the previously extracted local modes according to the entire pixels of the image.