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A Glimpse At Optical Character Recognition

Optical Character Recognition (OCR) is one of the few techniques that has achieved use throughout the entire industrial spectrum, resulting in immediate labor savings (which would otherwise be lost in laborious retyping of handwritten or typewritten data). With OCR, a large number of paper-based records in a variety of languages and formats may be digitized into device text, which not only simplifies storage (saving space, fireproofing, pest management, and so on) but also makes inaccessible material accessible to anybody with a click. It is indeed one of the best techniques used so far to convert image to text online. What are your kind thoughts on it?

The latest version of OCR is far more efficient in detecting and processing data than previous versions. Machine learning deserves all of the credit for expanding its capabilities by transforming data into session keys and tables that machines can manipulate. OCR has evolved into much more than a digital character gesture recognition that assists in the instant conversion of image to text online. It currently has a wide range of applications, including invoice processing, handwritten papers, bank checks, ID cards, forms, and more.

Anyways, let us come to the topic of discussion. In this read below, we will be talking about the OCR technology and its applications in various fields. 

Let’s move on!

What Is The Purpose of OCR Technology?

The transformation of handwritten text and paper artifacts into machine-readable text is the most popular and well-known application of OCR technology. After OCR processing, popular online Microsoft programs such as Microsoft Word, Open Office, and Google Docs can be used to edit scanned paper documents. This technique had to be done by hand before the arrival of OCR technology. In the case of ancient newspapers, prior to OCR technology, the only option to scan these old texts was to carefully rephrase all of the text, which was evidently a time-consuming and error-prone operation.

OCR technology can be utilized in banks for increased trading security and risk management, digitizing loan documents, and enabling two-layer encryption at ATMs that use facial recognition technology, in addition to transforming paper records into machine-readable texts. Furthermore, OCR technology is employed in domains that are less well-known, such as data input automation, document indexing for search engines, automatic number plate detection, and assisting those who are blind or visually impaired.

Application of OCR:

Increase The Speed With Which Customers Are Onboarded:

Every industry faces the difficulty of onboarding new employees. Manual data entry and data assessment of each people are required for identity verification, filling out application forms, and other associated operations. The system can automatically acquire, extract, validate, and customer data from the text using OCR and machine learning algorithms. It can also check the signatures of clients who are engaging in any type of legal transaction and convert its captured photo to text in moments. Software technology is real-time, cost-effective, and quick, with far more accuracy than manual verification.

Scanning of Invoices Using Intelligence:

Traditional OCR technology was resource-based, requiring data to be manually mapped to fields. The intelligent OCR technology can learn to recognize vendor invoices based on the layout and save the data in the system for future reference using AI / ML. It can also map the data to fields in each statement to extract only the values that are required while disregarding the rest. This may include transforming image to text that saves you a lot of time while you are looking for some kind of source that could help you do so.

If the supplier submits a paper invoice, advanced OCR can detect the invoice’s layout and extract the necessary information. If the supplier supplies an electronic file (an image of the invoice), clever OCR automatically scans the document and returns the same results as before.

Automatic Recognition of License Plates:

For congestion control, security systems incorporating OCR technology are utilized to capture the license plate in real-time and convert image to text format for storage. This information can also be used for access control and parking space management. With minimal to no human intervention, the system can index hundreds of automobiles in a parking space automatically. In addition, the system may check if the license plate is legitimate and issue an alert if any blacklisted plates are detected.

Categorization of Documents Automatically:

OCR software is used by law firms, medical practices, and other professional businesses to extract text from images and classify documents automatically. Multiple documents can be organized and classified using OCR software depending on the document’s keyword, theme, or any other predetermined factor. This has decreased the time-consuming manual document classification procedure that was previously necessary to sort and classify a large number of documents.

This technology can be extremely beneficial to huge hospitals, colleges, and enterprises. The operator must upload all of the documents into a single folder, after which the software will probably select, classify, and store them in the right category based on the document type.

Obtaining Information:

Another area where OCR technology has made a difference in information retrieval. When you physically pick a file and search for the essential data, retrieving data contained in non-digital/image format becomes more difficult. All paper and electronic data that machines can’t read will be translated into a machine-readable version and saved in the unified data directory once an OCR system is in place. This is due to the fast image to text conversion technology.

Furthermore, cloud-based data is more secure than traditional papers, which can be stolen, destroyed, or get damaged over time. Companies can store sensitive data in the cloud and safeguard it from illegal access with controlled access.

Benefits of Using OCR:

Improve Efficiency

Organizations benefit from OCR software since it allows for faster data extraction when needed. It allows companies to reduce data management time by up to 80%. When the manual process is abolished, employees are free to concentrate on other important aspects of the company. This has a significant impact on the company’s productivity.


After you convert image to text, you can save it in a variety of formats, including.doc,.rtf,.txt (the simplest),.pdf, and so on. Internally, these files can be searched by pressing Ctrl+F on a PC or Command+F on a Mac. You can make these documents internationally accessible by publishing them to an appropriate database, such as Google Drive (for personal use).

Enhanced Data Protection:

The potential of optical character recognition to increase data security, resulting in less unauthorized disclosure and suppression of crucial information, is one of the most significant advantages of the technology. With the help of AI and Machine Learning, OCR can automatically detect confidential material and secure it from unauthorized employees.

Furthermore, you can employ various security measures when converting paper documents to digital to prevent unauthorized personnel can read and editing the documents.


You could want to rewrite an old will or make repairs to an old term report you prepared. Instead of having to retype the entire document after it has been digitized with OCR(means converting a photo to text), you can quickly do this with a word processor.


Once a document has been scanned by OCR and stored in a common database, everyone with credentials to that database has access to it. This is especially handy for banks, which can examine a customer’s past cheques at any time and from any location in examining their credit history. Another obvious application is having government archives accessible from anywhere, so you can look up your property ownership history or your grandfather’s birth certificate.


Digitizing documents reduces the amount of space required for the same information on a server from a few cubic inches to a few bytes, potentially freeing up room for other productive uses (such as seating the employee tasked with OCR). In addition, the paper that has been deemed obsolete can now be recycled, lowering the cost (and consequently the cost) of the new paper.


Backups Instead of storing costly copies and duplicates in paper form, digital backups can be done quickly and potentially an endless number of times. When combined with the aforementioned, OCR makes paperwork much more sustainable.


Today’s OCR software can read a wide range of scripts, including Arabic, Indian scripts, and Japanese kanji. When combined with the Unicode standard and machine interpretation software (such as Google Translate), a document in one language can be captured, can be convert image to text, and translated into any other language, obviating the need for human translators to painstakingly pore over printed texts. As a result, business turnaround time is reduced.

OCR technology can be utilized in banks for increased trading security and risk management, converting image to text, and enabling two-layer encryption at ATMs that use facial recognition technology, in addition to transforming paper records into machine-readable texts. Furthermore, OCR technology is employed in domains that are less well-known, such as data input automation, document indexing for search engines, automatic number plate detection, and assisting those who are blind or visually impaired.

Disadvantages of OCR:

Quality Isn’t Always Guaranteed:

The quality of OCRed documents is one of the major drawbacks of optical character recognition. No doubt OCR is the best image to text converter available online, but the efficiency of OCR is determined by the quality of the image provided as input. This means that OCR will have a tougher time identifying text from an image if it contains any flaws. OCR faults are more difficult to remedy since they frequently require the user to rectify the OCR mistakes before re-processing with OCR.

It’s Time-Consuming and Costly:

OCR also has the disadvantage of being sluggish. This is due to the fact that OCR technology must evaluate and transform each image into text, which can take some time. A single page of text, for example, could take several moments to transform using OCR. Whether you need to convert a huge document to text, this can be an issue. Optical character recognition is also costly, and it isn’t always available for all pdf files.

Misrepresentative At Times:

Optical character recognition has a number of drawbacks, one of which is its inaccuracy. This is due to the fact that OCR technology is not perfect and might make mistakes when translating photos to text. For instance, OCR may misread a lowercase “l” as a “1” or a “b” as an “8.” If the text is utilized for crucial purposes, such as in a legal document, this can be problematic.

To ensure correctness, you may need to reread the text after OCR after you convert image to text.

Vulnerable To Errors:

Optical character recognition has a number of drawbacks, one of which is that it might introduce flaws that cause the document’s value to be misled. OCR can make mistakes, such as misinterpreting a symbol as a word or a line break. When an OCR engine converts text to text, it makes a character recognition error when it recognizes one character as another. The OCR may, for example, recognize “N” and transform it to “E.” This is a common occurrence in writings using non-English characters.

Scarcity of Information:

The absence of data on some characters, such as punctuation, is one of the issues with optical character recognition. Because they’re too little or non-contiguous, or they’re upside down and backward, many punctuation marks are unreadable by OCR software. Punctuation problems can also happen if the user uses the incorrect punctuation mark.

Some Languages Are Difficult To Understand:

If the text is in a tongue for which there is no OCR Language Pack, OCR may not be able to recognize it correctly. You can add OCR Language Packs to your OCR system as an optional component. To increase the results of the output, be sure that the OCR engine you’re using supports your language.

It’s Possible That You Won’t Be Able To Understand Right-to-Left Languages

One of the drawbacks of optical character recognition is that it may be unable to recognize right-to-left languages correctly. The following languages are not recognized by the OCR function: Japanese, Chinese, Korean, Arabic, and Hebrew.


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