1. Edge detection You can find edges in images by subtracting adjacent pixel values: edges show up where they are different. Whether this works depends on how sharp the edges are. Printed letters are very, very sharp. Most stains are not. More sophisticated is “spatial filtering” which is an exact analog of filtering sounds by frequency. Letters have high spatial frequency, and most staining will have low spatial frequency. I first saw this in work by Tamas Doszkocs at the National Library of Medicine.

2. Edge detection examples (Alan Ayckbourn; works quite well)

3. Less successful If you think about it, the cat doesn’t have any sharp edges, except for the claws; he has fur everywhere else, even on his ears (making me jealous in the winter). The whiskers are actually the most prominent part of the right-hand image.

4. Bloodstains Original spot, page 1 Edge detect, threshold Bleached (hydrogen peroxide)

5. Next page, worse stain Note stain over letters, and ballpoint pen writing on page Edge detection removes almost all the stain but also the pen writing The bleach damaged the paper (applied too heavily) but removed the stain without also erasing the ballpoint ink.

6. Conclusions Spatial filtering picks up edges but not broad areas; thus it selects letters. It’s a more sophisticated version of edge detection and might have done better. Once something is reduced to a fairly dim level, you can remove it with an intensity threshold. Color filtering is difficult: blood is not pure red. But I could have worked harder at that. Hydrogen peroxide was a lot faster than scanning, let alone experimenting with software. Of course, photocopy after bleaching, since the paper is now weaker (assuming you care).