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you know it's pretty easy to take words on your computer screen and put them on

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a physical sheet of paper just click print and unless you've forgotten to

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fork out an extortion level amount of money for a new cartridge you'll have

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fresh warm satisfying documents just a

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few moments later but going in the opposite direction scanning dead tree

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information into your pc is actually quite a bit trickier i mean sure flatbed

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scanners aren't all that difficult to operate per se

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but many of them are basically just taking a picture of the document and

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saving it onto your pc meaning not only will it probably not look very crisp due

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to file compression and little bits of dust in your scanner but you can't edit

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a clean copy of your document in your favorite word processor because the

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scanner won't recognize each individual character

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fortunately there are a number of devices out there that enable optical

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character recognition or ocr where each character on a page is scanned

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individually so your papers are uploaded as actual text documents instead of

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messy jpegs but how exactly does that

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work and is one kind of optical scanner better than another well because the

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whole concept of translating text into electronic signal is pretty broad there

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have been lots of different implementations of ocr over the years in

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fact one of the earliest electric ocr devices the optophone was invented all

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the way back in 1914 this bizarre looking contraption relied

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on the special behavior of selenium

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which conducts electricity differently in light and darkness

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as it scanned the words on a page the optophone distinguished between the dark

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ink of text and lighter blank spaces

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generating tones that corresponded to different letters making it possible for

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blind people to read with some practice

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later in 1931 a machine was developed that could convert printed text to

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telegraph code one of the first technologies to translate printed

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characters to electrical impulses rather than sounds but it wasn't until the

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1960s and 70s that ocr began to take a

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more familiar modern form with postal services using ocr to read addresses and

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software that could recognize many different fonts

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so back to present day when you scan a document how exactly does the software

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know what it's looking at well the first step is to cut out artifacts so your ocr

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program can concentrate on the text and nothing else so it attempts to remove

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dust and other various graphics align the text properly and convert any colors

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or shades of grey in the image to black and white only making the words

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themselves easier to recognize the next step is to figure out which characters

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are on the page simpler forms of ocr compare each scanned letter pixel by

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pixel to a known database of fonts and decide on the closest match smarter ocr

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however takes this step farther by breaking down each character down to

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constituent elements like curves and corners and looking for matching

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physical features and actual letters you can think of the differences between

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these two approaches similarly to the difference between raster and vector

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images which you can learn more about up here ocr software can also make use of a

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dictionary so it won't accidentally spit out nonsense words due to inaccurate

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scanning for example if your scanner sees this but it can't quite tell

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whether the middle letter is an o or an a it can check its own dictionary to

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decide that the word is actually dog and not dag giving ocr software situational

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information can further cut down on errors such as telling it to only try to

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match numbers if it's reading zip codes on an envelope

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even with these tricks however ocr obviously is not perfect which you've

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probably seen for yourself if you've ever used it but with greater

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processing power and machine learning techniques that allow software to

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recognize more subtle patterns over time ocr has become versatile enough to

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recognize harder to read typefaces inconsistently printed material and even

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handwriting and free ocr cloud processing services

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like google drive which has a lot more machine learning capability than your

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home pc for which i hope are fairly obvious reasons have made ocr more

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accessible than ever no word yet though on whether google will take it a step

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further and launch google interpretive dance translator

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about us section thanks for watching this video don't forget to like it or

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me