Just point your camera to the nice poem you have written and all goes into word file editable on a digital device. That’s the magic Optical Character Recognition a.k.a OCR is!
The technology has enhanced the features of a scanner as the traditional scanners were used to only create a copy of the scanned subject as a picture. The OCR System enhanced it by recognizing the letters in that scanned document and then by converting it into a word file.
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Data is generally passed to the computer by using a scanner or other hardware devices like a digital camera. Fax applications use OCR to transform incoming fax from graphics files into word documents. OCR is already being used widely. The task of typing a document from a handwritten source which once required hours or days to type can now be accomplished in a few seconds.
All OCR systems include an optical scanner for reading the text and sophisticated software for analyzing images. Most OCR systems use a combination of hardware and software to recognize characters while some systems do it entirely through software. Advanced OCR systems can read the text in a large variety of fonts, but they still have difficulty with handwritten text.
First, the program analyzes the structure of document image. It then divides the page into elements such as blocks of texts, tables, images, etc. The lines are divided into words and then – into characters.
Once the characters have been singled out, the program compares them with a set of pattern images. It advances numerous hypotheses about what this character is. Based on these hypotheses the program analyzes different variants of breaking of lines into words and words into characters. After processing huge number of such probabilistic hypotheses, the program finally takes the decision, presenting you the recognized text.
So, in a nutshell, it sees your first letter and compares it with all the symbols present in its database. So, if it resembles most with P, the software spits out P! And you need not worry, it has got thousands of different styles of P, just in case you have got an awful handwriting like me!
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Accuracy rates can be measured in several ways, and how they are measured can greatly affect the reported accuracy rate. For example, if word context (basically a lexicon of words) is not used to correct software finding non-existent words, a character error rate of 1% (99% accuracy) may result in an error rate of 5% (95% accuracy) or worse if the measurement is based on whether each whole word was recognized with no incorrect letters.
Recognition of Latin-script, typewritten text is still not 100% accurate even where clear imaging is available. One study based on recognition of 19th and early 20th century newspaper pages concluded that character-by-character OCR accuracy for commercial OCR software varied from 81% to 99%.
Total accuracy can be achieved by human review or Data Dictionary Authentication. Other areas—including recognition of hand printing, cursive handwriting, and printed text in other scripts (especially those East Asian language characters which have many strokes for a single character)—are still the subject of active research. The MNIST database is commonly used for testing systems’ ability to recognize handwritten digits.
Web-based OCR systems for recognizing hand-printed text on the fly have become well known as commercial products in the recent year. Accuracy rates of 80% to 90% on neat, clean hand-printed characters can be achieved by pen-computing software, but that accuracy rate still translates to dozens of errors per page, making the technology used only in very limited applications.
- Data entry for business documents.
- Automatic number plate recognition.
- Automatic insurance documents key information extraction.
- Extracting business card information from a contact list.
- More quickly make textual versions of printed documents.
- Make electronic images of printed documents searchable, e.g. Google Books
- Converting handwriting in real time to control a computer (pen computing)
- Assist technology for blind and visually impaired users
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