How OCR Technology Works to Extract text from Images?


How OCR Technology Works to Extract text from Images?
How OCR Technology Works to Extract text from Images?
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Despite the technology revolution, organizations continue to rely on paper documents to complete a variety of functions. When it comes to making changes to already prepared files, however, it becomes a significant issue.

As a result, many companies hire data entry professionals to manually enter all of the content from the papers and make any necessary revisions.

If you’re seeking the most efficient way to complete this activity, OCR technology is the greatest option. What is optical character recognition (OCR) technology and how does it work? What is the mechanism behind it? What is the advantage of extracting text from pictures with it?

You’ve come to the right place if you’re questioning these issues. We’ll take you to step by step through the process of converting an image to text.

What is OCR Technology: How does it Work?

OCR is a recent approach for obtaining the editable text from a photograph. When turning text in a picture into an accessible data file, OCR technology is intended to minimize the need for physical input.

OCR software can only distinguish a single type of font in the past; however, today’s modern OCR systems can convert photos with a variety of fonts into editable text.

This technology is based on powerful algorithms that analyze word patterns in images. Following this analysis, OCR programs capture and display text from photos in an editable format such as Word.

Scanning papers in their cleanest form is the best method to use OCR. If the image is blurry, OCR findings may be harmed because it will be difficult to display the words contained inside it.

OCR applications use a variety of techniques, but most focus on one character, phrase, or block of text at a time. The elements are then identified using one of two algorithms:

Pattern recognition: Examples of text in a range of fonts and formats are input into OCR software, which would then be compared and recognized as letters on the scanned page.

Feature detection: To recognize characters in a scanned document, OCR applications use rules based on the attributes of a single letter or number.

A comparative characteristic could be the number of inclined lines, crossed lines, or curves in a character, for example. The capital letter “A,” for example, might be encoded as two diagonal lines intersecting with a horizontal line in the center.

Does OCR Make a Document Accessible?

No, not really, is the quick response. Some OCR tools allow you to scan a document and convert it to a word processing document in one step, however, this does not guarantee that the material is accessible.

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After you’ve processed your document with OCR online, you’ll need to choose the text and read it to ensure that the procedure went smoothly and that the language is understandable.

It’s possible that you’ll need to spell check it, add headings, and tags, reorder it, and more. A word processor, like Word or Adobe Acrobat Pro, can be used to accomplish this.

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How Does It Create Documents?

Let’s get right to the point: how does it go through documents? What distinguishes an OCR device from others? How does it scan tangible text and convert it to soft copies or digital documents?

Keep in mind that OCR is not the same as a scanner as the ones found on printers. A scanner’s job is to scan documents, but an OCR device’s job is to scan documents letter by letter. In a suitable situation, a scanner effectively takes a photograph of a document.

By closing the lid on the top of the document and forcing it against the optical scanning lenses, the scanner produces this situation. OCR devices, on the other hand, use lenses to scan papers for characters and then convert them to words.

This is how it works in a document:

  1. Alignment De-Skewing

If you use OCR to scan a book, it must appear in a straight line on your selected device. When scanning a document, OCR de-skews the alignment before translating characters into words.

  1. Zoning Paragraphs

Because OCR recognizes the empty spaces on the page first, the spacing and shape of your document are important in this phase. This method allows the device to scan without being bothered by page numbers, watermarks, or supplementary text.

  1. Color Grading: Binarization

When you scan a document, it may appear deformed or hazy. By increasing the color-grading on your page, OCR technology prevents it. This approach allows the optical lens to swiftly interpret the text, regardless of color or font.

  1. Document Segmentation

The OCR device splits each word into groups, from longest to shortest, once the document is in perfect condition for word/character scans. It enables the program to scan the text and recognize each letter before combining them into words.

  1. Recognition of Scripts

Script recognition helps OCR to properly align documents. Apart from scanning characters, OCR’s main task is to align them correctly. If a character includes more than ten words, OCR can place it exactly where it belongs using script recognition.

  1. Post-Processing

This phase is where OCR adds final touches to the texts, combining words, arranging them together, etc.

Best Ways to Extract Text from Images

Use an Online Image to Text Converter

Many websites offer OCR applications that allow you to transform any image to text without requiring you to download any software or extensions. You may quickly upload any image to an online image to text converter and get editable text in a matter of seconds.

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This service can be accessed from any device because it is a web-based utility with no compatibility difficulties. Using a tool to convert images to text is a simple process.

After you’ve uploaded an image, all you would have to do is select the transform option. As a result, the backend’s powerful OCR engine will extract and display editable text in real-time. You can see the example below:

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Extract Text with Google Docs

Google Docs is also another useful tool for obtaining the text from photos. Google Docs includes an OCR feature that quickly converts images to text.

Every day, thousands of individuals use our online document creation service. You must first access Google Drive before using Google Docs to extract text.

You’ll be able to see the documents, photos, and other things that can be opened with a single click as soon as you log in to your account. If the image is already on your drive, right-click it and choose “Google Docs” from the “open with” tab.

The image will be accessed using Google Docs, and the extracted content will appear next to you as you open it.

Get OCR App for Android

As a smartphone user, you may find it challenging to complete a variety of tasks. Extracting text from photographs, on the other hand, is simple thanks to the availability of an image-to-text converter app for Android.

On the Google Play Store, you may find several free OCR programs. You can choose the best app after examining the reviews, ratings, and functionality of several available options.

You can upload the file and wait for the software to work its magic, and you will have a photo to text app on your iPhone. This strategy, like the others previously mentioned, will assist you in obtaining the required outcomes quickly.

How does OCR extract Text from an Image?

To recognize any writing within an image, an OCR requires three main steps.

These are the phases:

Preprocessing: Relevant text segments and text recognition are extracted during the preparation stage. Depending on the type of identification procedure and image, some features may be excluded.

●    The image has been rotated up and down.

●    Slanting and skewing are accomplished in different ways.

●    You can also utilize directional histograms to determine the text’s horizontal and vertical slopes.

●    Quantization is a technique for converting the color of each pixel to black and white.

●    Thinning is a technique for decreasing the number of bytes in a letter to just one.

●    We obtain the text skeleton via thinning.

●    Where necessary, thickening is done as well.

Segmentation: During the segmentation stage, the preprocessed text is cut into phrases, sentences, and letters.

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●    To begin, the device cuts each word in a sentence according to the likelihood of serial cuts.

●    The best cuts distinguish words that are close together.

●    When a term is spread or eliminated, lexical analysis replaces it with the best possible word.

●    A term recognition software uses algorithms to do semantic analysis.

Recognition: This is the most crucial aspect of any OCR because it is here that the text is recognized and converted to digital form inside a computer.

It uses a range of methods and strategies to classify a text.

Some of the tactics listed below could be used:

●    A soft computing strategy is used.

●    MLP is used to recognize characters.

●    Genetic algorithm with fuzziness.

●    Generic Neural networks.

OCR Improves Productivity

All your documents living in the digital environment improve productivity because any authorized user easily accesses them. There will be no more rummaging through large file drawers in backroom storage areas.

OCR Minimizes Errors

Every company strives to keep errors to a minimum. That is made possible through OCR! There will be no more transcribing errors or errors while copying from one document to another. You now have access to the original data.

OCR Saves Time

Time is money, so time-saving saves you a lot of money, a whole lot of money. Minimize your operating costs and you’ll have the most funds to invest in other areas, such as increasing market share or lowering expenses in current ones.

Where can OCR be Used?

This technology is fantastic since it can be applied to any industry that deals with text data. So, in essence, it covers all departments: Banking, operations & marketing, hr, purchasing, and legal are all departments that need to be addressed.

Here are a few examples of how OCR systems can be used:

●    Scanning printed papers into editable versions for text editors.

●    Search engine indexing of printed materials.

●    Data entry and processing are automated.

●    Documents are transcribed into text that can be read aloud to visually challenged people.

●    Data extraction and transmission to accounting software (receipts, invoices).

●    Legal documents that have been signed are transferred to an online format.

●    Letters are being sorted.

●    The words in a picture are converted into a certain dialect.

●    Searching for scanned books is possible.

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Conclusion:

When it comes to extracting text from scanned documents, OCR technology is a lifesaver because it saves you time and money. You can complete this operation using any of the image-to-text conversion methods outlined above without having to follow any complicated steps.

OCR is a tool that allows you to extract text from photos and files and alter it. Any business can begin using OCR to reduce manual labor. It will also result in increased earnings. For improved performance, OCR can be combined with other automation technologies.


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