Imagine you have piles upon piles of handwritten documents. There are a number of things you might want to do with those documents, such as searching for a particular subject or heading or even digitize them for later use. One way to go about it would be to sift through them and transcribe each document, word for word. But in the 21st century, you want a faster, simpler, more efficient, and more convenient solution. That is where optical character recognition (OCR) comes in, and here is what you need to know about it.
What Is OCR?
Optical character recognition, or OCR, is a technology that allows a computer to recognize text within images. When a computer processes an image, such as a scanned document or photograph, it identifies it as a series of adjacent dots (pixels) with different colors. However, when an OCR program is employed, it is able to parse those pixels, identify them as letters, and convert the handwritten text into a machine-readable form. Since the computer can then understand the document, data produced can be processed by other programs for different purposes.
The Uses of OCR
There are a lot of benefits and uses which can come from technology such as OCR. Today, OCR powers a lot of systems and services used, even in daily life. Common uses of OCR include simply making a record of data for future use, automatically recognizing number plates, and performing handwritten interactions with a computer. OCR software has similarly been built to cater to specific uses. The Tabscanner receipt OCR system is built around its ability to interpret and process data from receipts, and many others like it. The reason OCR has become so widely used is due to its ability to save time, increase efficiency, and improve automated reporting.
How OCR Works
An OCR system has to have an optical scanner as an integral component of the system since this is how it receives its input, the image. Once the system receives an input, it will attempt to analyze the image and identify the different characters within it. For most OCR systems, this is done by using both hardware and software in combination. Now, as you can imagine, for a computer program, recognizing a character is simpler said than done. If the document in question is typed, there can be different typefaces, whereas if it were handwritten, well, then the possibilities would be infinite.
To overcome this issue, OCR systems use either pattern recognition, where characters are compared to a stored database of others and recognized in their entirety, feature detection, where characters are identified by recognizing the individual lines and strokes which make them up, or a blend of the two.
As you can see, OCR systems are a popular technology as a result of how useful it can be. Tedious, time-consuming tasks such as manual data entry can now be completed in a fraction of the time, and reports produced in an instant. And now that you know more about OCR, you can ask for it should you need it, or identify when you see it.