Optical Character Recognition (OCR) technology has revolutionized our interaction with printed and handwritten text. It enables seamless digitization and automation. However, while the technology is widely used for English text, its adoption for regional languages like Hindi and Gujarati is unique and brings more opportunities. Hence, in this post, we will learn what OCR technology is, how it works, its advantages, disadvantages, benefits, and its role in operating in different languages.
What is OCR Technology?
Optical Character Recognition (OCR) is the process that can convert an image of text into a machine-readable text format. If you scan a paper, then your computer saves the scan as an image file. Further, you want to edit or count the words in the image file. However, you are not able to do it in the scanned image. Thus, in this case, OCR will help you convert the image into a text document, storing its contents as text data.
OCR Technology is beneficial as most businesses depend on it. Their workflow involves receiving large piles of information from different print media, including paper forms, invoices, scanned legal documents, and printed contracts.
It will be difficult if someone wants to store and manage these documents. Hence, OCR helps in many ways to manage paperless documents and to process the text in the images. It is also used in AI-based number plate detection, especially in Automatic Number Plate Recognition (ANPR) systems.
How Does OCR Technology Work?
Now that you know about OCR and how amazingly it operates and solves our problem. You may also wonder how this technology works. There are various steps involved in the operation of OCR software, including
Image Acquisition
The scanner reads the document and converts it into binary data whenever you insert the image or scan. Later, OCR software will analyze the scanned image and classify the light areas as background and the dark areas as text. That’s how it acquires the image and converts it into binary data.
Pre-Processing
the digital image is cleaned to remove extraneous pixels. This means the image will first be cleaned and then errors removed to prepare it for reading. Various cleaning techniques are involved, including deskewing or tilting the scanned document slightly to fix alignment issues during the scan. Despeckling or removing extra error spots and smoothing the edges of text images. Lastly, script recognition helps in multi-language OCR technology.
Text Recognition
This step typically involves aiming at one character, word, or text block at a time. These characters are then identified using one of two algorithms, either pattern recognition or feature recognition. These are the two main types of OCR algorithms or software processes.
Pattern Matching
Pattern matching helps to isolate a character image known as a glyph, and it compares with a similarly stored glyph. Pattern recognition works only if the stored glyph has a font and scale similar to the input glyph. Pattern matching works best with scanned images of documents typed in a known font.
Feature Extraction
the feature extraction will break down the glyphs into features such as lines, closed loops, line direction, and line intersections. Further, it then uses these features to search for the best or nearest match among its various stored glyphs.
Postprocessing
After the overall analysis, the OCR converts the extracted text data into a file format. Some OCR systems can annotate PDF files, including both the before and after versions of the scanned documents.
Types of OCR Technology
Once we understand the OCR technology, it is also essential to know the different types of OCR. So, there are four types of OCR programs:
Simple OCR
In simple OCR, analysis is done with character-by-character pattern-matching. It compares scanned characters to the stored glyphs. Later, it analyses different types of documents with various potential font and language combinations. However, simple OCR operates with certain limitations because there are unlimited font and handwriting styles, and each type cannot be captured perfectly and stored in the database.
Optical Mark Recognition (OMR)
If the system identifies checked boxes and other marks, such as bubbles in the forms, then all these marks can be identified by matching to stored images, as with simple OCR. It is highly used to recognize logos, watermarks, and other text that has symbols in a document.
Intelligent Character Recognition (ICR)
Nowadays, OCR systems use intelligent character recognition to read the text as humans do. They use progressive methods that train machines to behave like humans by using machine learning software. A system known as a neural network analyzes the text over many levels and processes the image repeatedly.
The system searches for image attributes, including curves, lines, intersections, and loops, and combines the results of all these different levels of analysis to get the final result. Even though ICR typically processes the images in one character at a time. The ICR technology operates fast and produces results in seconds.
Intelligent Word Recognition
Intelligent Word Recognition functions similarly to ICR. However, the process has been trained to recognize a word in a single image, making it faster.
Benefits of Optical Character Recognition (OCR) Technology
- The technology improves your productivity by utilizing OCR software; you can integrate document workflow within your business.
- It finds required documents quickly by searching for a specific term in the database, so you don’t have to sort through different files in a box manually.
- It can scan and read number plates and road signs in self-driving cars. In addition, it can detect different brand logos in social media posts or identify product packaging in advertising images.
- It can improve service by offering employees the most up-to-date information.
- The technology can automate document routing, content processing, and prepare for text mining.
Advantages and Disadvantages of OCR Technology
Advantages of OCR
- The Optical Character Recognition can read information with high accuracy and process information quickly.
- It takes less time to convert to the electronic form.
- The latest technology can recreate tables using the original layout.
- The process in OCR is much faster than that of manually typing information.
- It can be integrated with AI and automation to improve data processing in AI-driven applications.
- Modern OCR can recognise multiple languages, including complex scripts like Hindi, Gujarati, and Arabic, enhancing global usability.
Disadvantages of OCR
- It can work efficiently with printed text but not with handwritten text.
- The technology is expensive, and it requires a lot of storage space.
- The quality of the output for OCR depends on the quality of the image.
- OCR has a bit lower accuracy for regional languages if they connect characters.
- The simple version cannot re-create tables and columns or produce sites.
- Digitally sensitive documents can be vulnerable to cyber threats if not properly secured.
What Languages are Supported by Optical Character Recognition?
OCR has evolved, and it supports a wide range of languages. It is a powerful tool for global document digitization. It can recognize and process different languages, including English, Spanish, French, German, Chinese, Japanese, and Arabic. In addition, it can also operate on Hindi, Gujarati, and many other regional languages.
It has high accuracy due to standard fonts and a vast dataset for training in English and Spanish. However, accuracy can be slightly lower due to connected characters for languages with complex scripts such as Hindi, Gujarati, Tamil, and Bengali.
With technological advancement, the accuracy level is improving and bridging communication gaps across diverse linguistic landscapes.
Conclusion
Optical Character Recognition (OCR) Technology is advancing rapidly, improving information representation and model optimization. Now, technology can analyze layouts, read order in complex documents, understand visuals, and represent them as charts and diagrams. Lastly, the technology works smoothly when translating Hindi or Gujarati text into English.
Many mobile apps, including Google Lens and Adobe Scan, support OCR for English and regional languages. If you want to integrate regional languages on your website or web application, hire the experts at iBoon Technologies. You can get a high-quality and cost-effective digital solution.
FAQs
Does OCR Technology Work For Regional Languages Like Hindi And Gujarati?
Yes, the technology supports different regional languages, including Hindi and Gujarati. Advanced systems, such as Google Vision and Tesseract, are well-trained and can recognise different scripts. The accuracy depends on various factors like font type, image quality, and text formatting.
Is OCR Accuracy The Same For English And Regional Languages?
No, OCR accuracy is higher for English than for other regional languages like Hindi and Gujarati. The English text benefits from OCR model training, standardized font, and simple script structures. In contrast, Hindi and Gujarati have complex scripts, connected characters, and variations in handwriting, making recognition more challenging.
Is Optical Character Recognition Available For Mobile Devices?
Yes, the technology operates for mobile devices through apps like Google Lens, Adobe Scan, and Microsoft Office Lens. These apps will allow users to scan printed or handwritten text and convert it into editable digital text. Many OCR apps now support multiple languages, including Hindi and Gujarati.
