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  • 24 Feb, 2024

Optical Character Recognition, also known as OCR, is a technology that helps convert data present in an image into a text format that a machine/computer can easily read, edit, and store. This technology is used to convert physical documents or digital images into editable text documents.

Since its first commercial development in 1974, the technology has evolved a lot. Now, it finds its application in almost every area of life whether it is education institutes, supermarkets, banks, and other businesses.

This blog of ours is going to provide you with valuable information about Optical Character Recognition. From its introduction to how it actually converts a text present in an image into an editable text, let’s decipher the functionality of this revolutionary technology.

What is Optical Character Recognition (OCR)?

As the name Optical Character Recognition indicates, OCR is a technology that optically recognizes characters present in a digital image. It converts physically written text, or text present in an image, into a digitalized form. This digital text, then, can easily be stored, shared, edited, and searched.

Let’s understand it with a general example. A teacher writes an entire lecture on the board and asks students to note it. Students take pictures of the lecture instead of physically noting it down.

Now, to convert the written lecture in the image into a text form that students can store and edit on their computers, they are going to need an OCR tool to perform this task. that is because the computer is not going to recognize the text present in the image let alone edit and share it. The OCR tool knows how to convert image text into digitalized form so that the computer can recognize it. once done, students can easily edit, share, or store this text on their computers. That’s what OCR technology is all about.

How Does Optical Character Recognition Work?

The example we just discussed was a general one. OCR technology is being used to process data much bigger than just a lecture. It’s being used in business, education, commerce…you name it.

Even though OCR finds its application in some of the major areas, its basic functionality is simple.

We’re going to break down its functionality in different steps so you can understand how it actually works.

Step 1 – Receiving a Digital Image:

In the first step, the OCR tool receives the provided digital image. This can be a scanned document or a photograph. If the information is present on a physical document, you can use a scanner to scan and convert it into a digital image. If the information is present in a photograph, simply upload it on the tool from your device.

Step 2 – Processing Image Quality:

Once the OCR tool has received your provided image, it analyses it to determine whether the image needs to be processed or not. The quality of the image matters when you have to effectively extract text from it. If there’s any need to enhance the image quality, some tools do it on their own according to the requirements. The changes depend on the nature of the provided image. Some common changes include:

  • Straightening the Image: This step is mostly used in the physically scanned document images. This involves adjusting the image that may have been skewed while scanning at a specific angle.

  • Reduction of Noise: If the image is too noisy, the tool makes necessary changes to reduce it. this helps the tool recognize the shapes of the text present in the image which helps it extract the text effectively.

  • Binarization of the Image: This is an important change that OCR tools make in the image to extract text from it. this step includes the conversion of a normal image into a black-and-white one. That is because most Optical Character Recognition tools are designed to effectively identify text present in a black-and-white image.

Step 3 – Recognition of Text:

Once the tool has processed the image according to its requirements, it starts analyzing it to recognize the text. Each character present in the writing is recognized individually for better results.

But how actually?

Well, it depends on the nature of the tool. there are various techniques that OCR tools employ to recognize text in an image. However, we are only going to discuss the ones that are most commonly used.

  • The Pattern Matching Technique: The pattern-matching technique is simple. It involves using a huge dataset of already fed characters in the tool. The tool matches the text in an image and compares it with the stored data set.

Here’s how it actually works. The stored data is stored in the tool by providing it with some images that already contain text in it. the text present in these labeled images is manually identified. This helps OCR train to extract text from the provided images. After the tool is trained, it performs the pattern-matching technique to extract data from digital images. It compares the characters with already existing ones and identifies them accordingly.

  • The Feature Extraction Technique: The second method that most OCR tools employ to convert an image into text is the feature extraction technique. It is a little complicated method. In this technique, the tool looks for different features of a character to recognize it. These features include loops, curves, lines, dots, etc. Let’s understand this with the help of an example. The example is general, and the OCR tool may or may not perform like this. We are using this example only for you to understand what feature extraction actually means. For example, if the image has a certain 3 horizontal and one vertical line, the tool is going to predict that the identified character is “E”. Similarly if the character contains a slight curve at the bottom of it and a circle on top of it, the character may be “g”. This is how an OCR tool identifies text present in a digital image by using the feature extraction technique.

Step 4 – Combining the Characters:

After the tool has recognized individual characters present in the image, it combines these characters to form words. In most cases, the OCR tool converts the words as they are. However, if the written text is not clearly understandable for the tool, it uses different techniques (depending on the nature of the tool) to combine the characters to form words. Some common techniques include:

  • By using a Language Model Ai
  • By using a dictionary
  • By analyzing the text contextually

Once the characters are combined, the tool converts them into digitalized texts. A postprocessing step also includes some tools which is all about proofreading and making sure there are no mistakes made in the conversion process.


Here’s what we have discussed in this blog. Optical Character Recognition technology is used to convert data present in a digital image into an editable text. This technology is being used in many areas such as business, finance, commerce, education, etc. Although the applications of this revolutionary technology are diverse, its basic working mechanism is almost the same. A detailed note is provided about the steps involved in the procedure of converting images into text is given in the information above.

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