The A-to-Z Guide to Text Detection
Use Cases

The A-to-Z Guide to Text Detection

This guide covers text detection definition, use cases of OCR, benefits of text detection, best text detection solutions, and more.
Alan Kilich
7 minutes

The A-to-Z Guide to Text Detection

In this era of digitization, the need for extracting textual data from different sources has risen to a large extent. Fortunately, recent advances in Computer Vision allow us to make great strides in easing the burden of text detection and other document analysis and understanding.

Text Detection is a technique used in computer vision to extract text from images or scanned documents so that it may be read, searched, and processed like any other kind of text.

This guide will cover everything you need to know about text detection:

  • What is text detection? 
  • How does text detection work?
  • Why is text detection important?
  • The benefits of text detection
  • Text detection use cases

What is Text Detection? 

text detection

Text detection, also known as OCR, is the process of locating written text inside an image and then enclosing that text into a bounding box with a rectangular shape. Text detection looks for text in an image. In contrast, text localization identifies where the text is and groups it into text regions by removing as much of the background as possible. 

Both image-based and frequency-based algorithms can be used to recognize text. Image-based methods are used in the process of segmenting pictures into many parts.

How Does Text Detection Work?

Scanners are used in Text Detection to process the actual printed form of a document. When the whole manuscript has been copied, text-detecting software takes it from color to black and white. By analyzing the scanned picture or bitmap for bright and dark regions, we can separate the characters that need to be recognized from the backdrop. Letters and numbers are extracted from the shadows using a computer algorithm. At this point, you should be focusing on a single character, word, or section of text. Next, an algorithm based on either pattern recognition or feature recognition is used to determine the identity of the characters.

The text detection tool uses pattern recognition to compare and identify characters in the scanned document or image file using text samples in different fonts and formats.

To identify letters and numbers in a scanned document, feature detection happens when the text detection uses rules based on the characteristics of those letters and numbers. A character's features include the number of straight lines, crossing lines, and curves it contains. For instance, the uppercase letter "A" represents two intersecting diagonal lines and a central horizontal line. To facilitate subsequent manipulations, computers translate each detected character into its corresponding ASCII code (American Standard Code for Information Interchange).

It is also the task of text detection software to examine the anatomy of a scanned document. It separates the page into sections for different purposes, such as displaying tables or graphics. Each line is broken down into words, and then each word is broken down into characters. After the characters have been extracted, the software checks them against a database of pattern pictures. The recognized text is shown once the software has evaluated all possible matches.

Why is Text Detection Important?

Print media is still widely used as a source of incoming information in corporate processes. Papers such as paper forms, invoices, scanned legal documents, and printed contracts are commonplace in the business world. It takes a lot of time and space to have all of this material on hand and organized.

Paperless document management has several advantages, but converting paper documents into digital images presents certain difficulties. Processes that rely heavily on human involvement tend to be laborious and time-consuming.

In addition, picture files are produced with the text included when this data is digitized. Word processing programs may not work well with pictures containing text. The issue is resolved by text-detection technology, which extracts text from images and converts them into text data for further analysis by other business programs. The data can then be analyzed, streamlined operations and procedures automated, and increased productivity.

text detection technology

The Benefits of Text Detection

Text detection technology's biggest benefit is that it simplifies data input by allowing text searches, editing, and storing. By storing documents on desktops, notebooks, and mobile devices, organizations and people have easy access to critical records at all times, thanks to text detection.

The following are some of the advantages of using text detection technology:

  • Save money
  • Data centralization and security (no fires, break-ins, or documents lost in the back vaults)
  • Document processing and distribution can be automated.
  • Service quality can be increased if employees are provided with correct, up-to-date information.
  • Increase productivity by speeding up processes

Let's look at other benefits of text detection:

Text detection technology is often used to automatically turn an image-based PDF, TIFF, or JPG file into a text-based file that a computer can read. Digital files processed using text detection can include receipts, contracts, invoices, and financial statements.

  • Searched a large database to find the right document.
  • Each document can be looked at and searched within.
  • Text that was taken out was sent to other systems.
  • When corrections need to be made, the text is edited.

Text Detection Use Cases

The most common use of text detection is the digitization of handwritten materials. After a scanned paper document has been processed using text recognition software, the text can be altered in a word processor like Microsoft Word or Google Docs.

Many of the tools and services we rely on every day are secretly powered by text detection. Passports, license plates, bills, bank statements, business cards, and automated number plate identification are just a few examples of documents that may be indexed for search engines using text detection technologies.

By digitizing paper and picture documents into machine-readable, searchable pdf files, text detection facilitates the optimization of big-data modeling. Unless text detection is applied to documents where text layers are not already present, automated processing and retrieval of relevant information cannot be achieved.

The ability to read customer data from bank statements, contracts, and other essential printed documents is a huge step forward for text recognition, which allows scanned documents to be incorporated into a big-data system. Text recognition allows businesses to automate the input step of data mining, eliminating the need for workers to manually inspect large volumes of picture documents and feed inputs into a big data processing pipeline. Image formats such as JPEG, PNG, BMP, TIFF, and PDF are all supported by text detection software, as is the saving of the extracted text as a text file.

Applications for Text Detection Technology

Many of the tools and services we use every day rely on Text Detection, but we do not frequently think about the technology behind them. There is a variety of lesser-known but no less crucial applications for Text Detection technology:

  • Recognizable passports at airport checkpoints
  • Knowing how to read road signs
  • Information gathering through document or business card extraction
  • Making handwritten notes searchable by computers Bypassing CAPTCHA anti-bot measures
  • Creating a searchable database of electronic publications like Google Books and PDFs
  • The input of data for official records (bank statements, invoices, receipts)
  • Eye-reading devices
Computer Vision based Text Detection technology

Text Detection technology has greatly facilitated access to these previously inaccessible documents, which has been used for digitizing historical newspapers and writings into fully searchable versions.

There are other ways text detection can help:

  • There are many ways to use text detection software that can not only help you with your work but also make your life better.
  • For people who are blind or have problems seeing, text detection software can help read text from scanned documents out loud based on your instructions.
  • Text detection can also help people who have trouble learning, like those with dyslexia. Text detection is used in schools all over the world. If you are a teacher and have students with developmental disabilities in your virtual classes, text detection can ensure that communication is clear and effective.

How Can Cameralyze Help You With Text Detection?

As we can see how text detection benefits businesses, it is time to introduce you to Cameralyze, where you can get help with text detection.

The Cameralyze OCR solution lets you detect and transform embedded or superimposed text inside media into searchable digital form. Using Cameralyze's no-code platform, you can quickly and easily create your own basic text detection app according to your requirements. It will take you no more than three minutes to incorporate the platform into your own system or through API because of the ready-to-use AI components feature.

The artificial intelligence OCR app contains a Computer Vision subfield that focuses on locating and converting letters, words, and paragraphs in pictures using optical character recognition with the maximum speed and accuracy possible (OCR). 

The application of machine learning and AI allows for the automated pre-processing and recognition of text in several languages. Cameralyze uses machine learning to transform scanned documents into digital text with exceptional speed and precision.

It was designed to preserve anonymity. Cameralyze Text detection solution ensures the privacy and safety of your data. It does not store any data, so you don't have to worry about privacy.

Start to use it for free now!

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