OCR stands for Optical Character Recognition and is the technology that is used for smartly scanning and converting the matter present in printed sheets or handwritten documents into digitized text. The oldest form of OCR dates back to 1928, when Gustav Tauschek, a scientist from Vienna, Austria patented a ‘reading machine’ in which photocells would recognize patterns on cards. With the technology being used in multiple settings in a variety of different ways, we get queries from many people asking what does OCR means on a scanner or what an OCR Scanner is? To let more people know about this revolutionary technology and how this function can benefit individuals and companies alike, here’s a guide to tell you everything about Optical Character Recognition.
You can think of Optical Character Recognition as an image processing application where the scanning of documents is completed with the purpose of converting text into digitized forms. The need for developing an Optical Character Recognition software aroused when errors in typing the written data or information present in printed documents started increasing significantly.
Along with this, the increasing tediousness of manually typing the information escalated tremendously owing to the large data influx in modern-day organizations. With OCR software, the conversion gets completed within seconds and with changing technology, the addition of Artificial Intelligence in the same makes it possible to generate insights simultaneously with the help of Machine Learning.
Routine OCR scanner process gets completed in the following steps:
For scanning to be precise and accurate, a decent physical copy of the required document is necessary. Even if you have an old typewritten document that isn’t as clear as you’d want, try methods like obtaining a colored photocopy of the same before you try your hand at OCR scanner process. This way, you end up improving the contrast between the written matter and the background, making it easier for the software to pick up and recognize the characters. The original print quality of the document has significant and direct impacts on the accuracy of the OCR performance.
The next step for OCR scanner is to run the document through an optical scanner. Again, the type and quality of the OCR scanner are important for the success of the OCR process. In general, Sheet-feed scanners are considered better for OCR scanner because they scan pages in a sequence, one at a time. This makes them a better option than flatbed scanners because most OCR applications require you to present a clear copy before expecting accurate results. Moreover, the only way to run pages through a flatbed scanner one at a time is to manually enter each page separately, which in itself is a time-consuming process.
Converting the image into a black-and-white format is the first step prior to the actual character recognition. Essentially optical character recognition is a binary process which means that the character identification is based on the fact that whether a feature is present or not. So, by reducing the image to a black-and-white format, we help in creating a binary environment where anything which is in black will be recognized as a character, while everything in white would be treated as the background.
However, this particular stage of the scanning process is not free of errors. For instance, if your document has any kind of stains on it, then on reducing it to the black-and-white format, even the stain would get reflected in a black shade. This means that along with the text or the characters, even the disturbance created by the stain will be recognized and converted by the application.
Every type of optical character recognition application works by reading and recognizing the document character by character, then completing each line, and ultimately the page. The difference between applications lies in the speed with which they complete this process. For instance, those applications that were designed in the mid-1990s were so slow that you could actually see the software reading each character over several seconds. Today, with better technology and the inclusion of Artificial Intelligence, recognition based on ML models has made the process lightning fast.
KlearStack has been a frontrunner when it comes to developing modern OCR solutions that are result-oriented. With our expertise in AI-based OCR scanner technology, we have helped businesses extract desirable data from tonnes of documents with ease and convenience, irrespective of its types, formats and text placements. Moreover, with our trained Machine Learning models that identify characters in a jiffy, the process gets further expedited. Not just this, the errors in the final output are also corrected by the use of our software, giving you the most validated and useful results every time.