By digitizing the document’s content, text-encased image files are produced. Word processing software cannot process text in photos the same way it does text documents. By transforming text photos into text data that can be evaluated by other business tools, OCR technology finds a solution to the issue. The data can then be used to perform analytics, declutter operations, automate procedures, and boost efficiency.
What is OCR?
OCR stands for Optical Character Recognition. It is the procedure that transforms a text image into a text format that can be read by computers. Your computer will save the scan as an image file, for instance, if you scan an invoice or a receipt. The phrases contained in the image file cannot be edited, searched for or counted using a text editor. The image can be transformed into a text file with its contents saved as text data using OCR.
Applications of OCR
- Mobile Banking Applications: Applications of mobile banking use OCR to capture and recover data from cheques for deposit.
- Healthcare records: OCR is used in the healthcare department to manage the information of the patient so that healthcare facilities can be
- Scanners for business cards: Apps with OCR capabilities can scan cards for business and save contacts right into the consumer’s address book.
- Recognition of License plate number: OCR technology is used by parking lots and law enforcement to read and recognize license plates for safety and parking management.
- Mails: Sorting and processing of mail according to addresses and ZIP codes is done automatically by postal services using OCR.
- accessed quickly.
History of OCR
OCR was invented by Ray Kurzweil in 1974. He invented it to read text printed in almost any font. It carried on developing, gaining from advancements in computer vision, artificial intelligence and machine learning. As a result, there was an improvement in accuracy and the capacity to identify more fonts and languages. With the introduction of smartphones and mobile apps, a larger audience now has access to OCR for activities like text recognition from photos.
Working of OCR
It processes a document’s physical form using a scanner. OCR software turns the written material into a two-color or white and black version after all pages have been copied. The scanned-in image is examined for bright and dark parts, with the light areas being classified as background and the dark areas as characters that need to be identified. After processing the black regions, alphabetical or numerical are discovered. During this phase, you usually focus on one character, word or section of text at a time. Then, two algorithms – pattern recognition or feature recognition used to identify the characters.
Advantages of OCR
- Text digitization: OCR transforms printed or handwritten text into a digital format that is machine readable and can be easily stored, edited and manipulated.
- Searchability: It enables users to rapidly find specific information inside big document collections by making scanned documents and images searchable.
- Time and Money Savings: By automating OCR, businesses may cut back on the time and money spent on manually entering information and document management.
- Archiving and document management: It makes it easier to digitize paper records and archives, which lowers the need for physical storage and enhances document retrieval.
- Multilingual Support: Numerous OCR systems include multilingual support, making them useful for multinational corporations and organizations.
Disadvantages of OCR
- Proofreading: It is necessary since errors may still be present in the output, even with high-quality OCR. Thus, hand proofreading is frequently required, especially for important texts.
- Handwriting Recognition: OCR technology may, in some cases, identify handwritten text, however it often performs less well in this area when compared to printed text.
- Security Concerns: OCR technology has the potential to be taken advantage of offensively to extract private information from papers.
- Cost: Premium OCR software might be costly, and commercial solutions may require continuous licensing or subscription fees.
- Limited Context Understanding: These systems frequently lack context awareness, which can cause them to misread words or phrases whose meanings depend on the context of the surrounding text.
Conclusion
With its many advantages for accessibility, data processing and document management, OCR is a powerful tool that links printed and digital text. In our digital environment, it is still a transforming tool.
FAQs on OCR
Q.1: Is OCR considered as an input device?
Answer:
Yes, OCR is considered as an input device as it is used to read the text that is printed.
Q.2: Is OCR- software or hardware?
Answer:
OCR is both, software and hardware systems as these can turn the physical documents into machine-readable form.
Q.3: What is the applicationof OCR?
Answer:
It is used in digitizing printed documents and for the recognition of license plate numbers on automated tolls and parking management.
Q.4: What is main features of OCR?
Answer:
Generally, OCR has a modular architecture that is open, scalable and workflow controlled.
Q.5: Which language is used in OCR?
Answer:
By nature OCR is a computer vision problem, OCR mainly using the Python programming language.