When researching Enterprise Content Management capture projects, the question of handwriting recognition comes up again and again — and many people aren’t sure what to expect. More commonly, their expectations are unrealistic. They think there is no hope at all, ever. On the other end of the spectrum, some think that tiny fevered cursive scribblings from a rushed meeting can be scanned (or even faxed) and read with accuracy. In helping people think about their forms and the viability of capturing handwriting, I have a few simple guidelines to consider which seem to apply in a majority of cases.
- Are handwritten forms really the only option? If the form is available online, can the data be made “fillable” and then submitted directly to your database tables? Can you let the user fill the form online and print, thus producing machine print and eliminating handwriting? How about taking the data that a user entered and bar coding it (if the form must be printed rather than be submitted)? Also helpful and sometimes overlooked: prefilling form data from your database through a merge process with a bar code index for retrieval of that same data.
- Does your Capture software support ICR? Intelligent Character Recognition (ICR) is what you need to read handwriting. Optical Character Recognition (OCR) is much more common and is designed to read machine print. Please don’t try to make it read handwriting – you won’t like the results!
- Make sure the handwriting is constrained. Annoying? Perhaps. But making the person filling the form write in boxes sets you up for the most successful ICR results. The catch phrase here could be “Curse the cursive”. When a character is joined to another character it is faster to write. However, the ICR software really struggles to figure out where one character starts and another stops. And here’s where recognition tanks. With the real world example below, we can generally expect 100% recognition.
- Ask for all caps handwriting. You can often tell your ICR engine to look for upper case characters only. This really
increases accuracy. And when the form filler forgets to write AS IF SHOUTING, you can often get OK results anyway.
- Show them how! I know it may seem condescending, but consider this a helpful reminder to those who would blow through the blocks in a mad dash. Show users an example of the way to write in constrained print fields. And here’s where you can tell them to use all-caps, and show it in your example.
- Use key index values and database lookups! If there is an employee number, unique phone number, SSN/TaxID, or other unique ID for the person filling the form, use it whenever you can. Then perform a database lookup to confirm identity and optionally populate any other fields that you may need that happen to exist already in your database.
- Less is More. People burn out on filling lengthy forms using constrained print fields. Try to minimze the amount the need to write and careless handwriting will decrease.
- Comb fields can work too. If you think all those constrained print boxes are just too hideous looking, try using comb fields instead. But remember, as soon as people ignore the combs and write cursively or sloppily, ICR results plummet.
- Use Drop Out Colors for the boxes. If your scanner and ICR software support color dropout technology, you make the ICR engine’s job easier. The boxes aren’t recognized by the scanner, but the handwriting is. So now the constrained print box lines (which make sure each handwritten character is isolated in a target area) don’t have to be considered during ICR.
- Use OMR bubbles if you really really need perfect index value from handwriting. Remember filling page one of standardized test? This painful process might be worth it. This is called Optical Mark Recognition. Since the engine just needs to confirm if a bubble is filled or not, this is easier and more accurate than OCR or ICR.
- Faxing? Well, OK. But recognition levels will go down.
With these hints in mind, you can look forward to results that are perhaps short of miraculous – that is, less accurate than OCR. By all means, the results are still worthwhile and produce great time savings when properly implemented. There are more tricks to describe, which I may save for a later blog. Please contact ImageSource if you have any questions about capturing handwriting in forms.