A robust faint line detection and enhancement algorithm for mural images

Mural images are noisy and consist of faint and broken lines. Here we propose a novel technique for straight and curve line detection and also an enhancement algorithm for deteriorated mural images. First we compute some statistics on gray image using oriented templates. The outcome of the process are taken as a strength of the line at each pixel. As a result some unwanted lines are also detected in the texture region. Based on Gestalt law of continuity we propose an anisotropic refinement to strengthen the true lines and to suppress the unwanted ones. A modified bilateral filter is employed to remove the noises. Experimental result shows that the approach is robust to restore the lines in the mural images.