Randall Munroe's handwriting is a bit difficult to OCR because a lot of the letters are smushed together close enough that the it's not possible to unambiguously segment the text into distinct letters (which is a necessary first step in any OCR engine that I'm aware of). Maybe Google's (or Vicarious's) magical convolutional neural net that can solve CAPTCHAs would fare better.
> it's not possible to unambiguously segment the text into distinct letters (which is a necessary first step in any OCR engine that I'm aware of)
This made me realize I never saw such a thing as OWR, i.e. a software that would first try to recognized whole words, then go down to character level if no satisfying match found.
> it's not possible to unambiguously segment the text into distinct letters (which is a necessary first step in any OCR engine that I'm aware of)
In my experience, the ability to handle overlapping letters (which is very common on type-written text and professionally typeset material) is one of the key things that separate the relatively lightweight OCRs (like Ocrad and GOCR) from the big complicated ones (Tesseract, Cuneiform, Abbyy etc). Whitespace character segmentation cannot be taken for granted if you want to do any useful OCR of "historical" material.