Highlight removal for camera captured documents based on image stitching

In camera captured document image analysis, specular highlights on glossy document surfaces often have negative effects on state-of-the-art Optical Character Recognition systems. Traditional highlight removal methods rely on either texture information from a single image or specific hardware setups to fuse complementary visual cues from multiple images. Motivated by the image stitching approaches to seamless panorama creation, we propose to remove specular highlights by capturing a pair of images from two viewing angles and merge their specular-free regions to produce an enhanced image eligible for character recognition. Compared to traditional solutions, our stitching based method can deal with document images with severe specular highlights, and eliminate the need for specific hardware devices or rigorous setup. Experimental results on various glossy document images demonstrate the effectiveness and efficiency of our method.