Table of Contents
The Optical Character Recognition technology, known as OCR, has been around for quite a while. But have you ever thought about how exactly a machine recognizes hand-written or printed characters and successfully processes them? Below we provide an overview of the OCR algorithms working process and explain what value this technology might bring to a business.
What is OCR?
According to the most common definition, optical character recognition is an electronic conversion of typed, printed, or handwritten text into machine-readable text. Examples include processing text on road signs, hand-written documents, or photos. The OCR technology can greatly benefit some businesses, especially the ones dealing with lots of handwritten or printed copy.
OCR use cases
The industries that can benefit the most from the use of OCR technology include banking, legal, and healthcare. All of them involve thorough work with handwritten or printed documents (cheques for banking, health records in healthcare, all paper documents in legal establishments) and therefore, the use of OCR can not only add accuracy to the data processing but make it faster and much more efficient. As well, OCR can be successfully used in supply chain management as you can program the OCR tool to read barcodes and recognize expiration dates, serial numbers, and similar sorts of data.
One more common use case for the OCR technology is the recognition of license plates. The use of this technology can be a great asset for police departments as it allows instant search for the needed vehicle and eliminates the need to manually search through records.
The backstage of OCR algorithms: how do they work?
There are multiple steps involved in the process of optical character recognition. Let’s have a look at every stage of it and see how exactly the algorithms recognize the text.
Image pre-processing
Before analyzing the image and the content that it contains, the OCR tool first has to “clean” the image in order to improve the recognition process and make the text clearer. Pre-processing may include:
- Image alignment: if the image is a bit tilted or was not aligned correctly, the program will align it in order to make the text lines 100% horizontal and/or vertical.
- Image despeckling: this means removing positive and negative spots and making the edges more smooth.
- Line cleaning: removing lines and/or non-glyph boxes.
- Image zoning: the software will identify columns and paragraphs as blocks and will use them in the recognition process correspondingly.
- Binarization: once the image is cleared, the program will make it black and white (binary) for easier recognition of characters.
Feature extraction and binary matrix creation
Once the image is “cleaned” from clutter and is made more readable, the OCR software will perform feature extraction aka actual character recognition. The software can do so either by evaluating distinct lines and strokes in order to define a character or by identifying the entire character at once.
Remember we mentioned binarization? Once the image is black and white, the software will then define empty (white) areas and black areas (which will be parts of the character). The image will then be converted into a binary matrix where black pixels will be 1s and white pixels will be 0s. After that, the software will use a distance formula to calculate the distance between the matrix center and the farthest 1s.
This is needed to create a circle of the defined radius which will later be broken down into smaller segments. In this way, each segment will contain a certain number of 0s and 1s. The software can then compare each segment with the ones stored in the database and identify the corresponding character.
Verification
Since there is a huge variety of fonts and writing styles, a machine can make mistakes in recognizing the characters. This is why it’s important to perform post-processing verification and either confirm the recognition or feed corrections to the machine for further learning.
The benefits of OCR for business
There are numerous tangible benefits that optical character recognition can bring to a business. Below we discuss the most important advantages of deploying OCR technology in your processes.
Resolved storage issues
Physical storage mediums such as paper files usually take too much space in the storage. As well, it’s quite challenging to properly organize and classify them, especially if there are too many files. By using OCR technology, you can efficiently convert all physical files into electronic records and store them in the cloud (or other preferred storage). You can also apply machine learning or automation to sort and organize your electronic documents and thus save a significant amount of time.
Higher security
Storage of your documents in electronic form not only brings higher efficiency and speed but also improves the security of the data. While physical storage can be hacked or accessed quite easily, it will be much more difficult to access cloud storage. Hence, by converting your documents into electronic form, you enhance their security greatly. As well, don’t forget about reliable and secure backups that you can create for your electronic documents.
High accessibility and searchability
It may not be very convenient searching through massive amounts of paper files even if they are properly organized. But with electronic storage, the search can be completed with a few clicks only – no need to say how efficient and time-saving it is.
The OCR technology allows you to convert your physical documents into any convenient format. In this way, your files become instantly searchable and accessible and you will be able to retrieve the needed information at any time.
Summing up
An OCR-based software can become a valuable tool for a business, especially if it deals with numerous handwritten and printed documents. While there are many OCR tools available in the market, you can also request the development of custom OCR software to serve your specific and unique needs. Contact us to learn more and we will gladly answer any questions that you might still have about the implementation of optical character recognition in your business.
Comments