We’ve said it a million times, and we’ll never tire of saying it: identity verification is fundamental for ensuring the security and protection of our personal data. For this reason, OCR technology emerged as a revolutionary tool that streamlines and improves this crucial process.

Have you ever wondered how it’s possible for a machine to read and recognize printed text on documents? Or how OCR is used to verify our identity quickly and accurately? In this article, we’re going to delve into what OCR technology is and how it’s used in identity verification, hopefully clearing up any doubts you may have!

What is OCR Technology?

OCR technology, short for Optical Character Recognition, is a system designed to convert printed or handwritten text into editable electronic data, enabling machines to understand and analyze textual content in an automated manner.

The basic idea behind OCR is to emulate the human ability to read and comprehend texts. Yes, you read that right. To do so, OCR uses algorithms and models to recognize and extract characters from an image or scanned document, converting them into digital text that can be manipulated and processed by a computer. This is made possible thanks to artificial intelligence.

This technology has evolved significantly over the years, thanks to advancements in machine learning and artificial intelligence. From the early steps of Raymond Kurzweil, the accuracy and speed of OCR have improved tremendously. 

Nowadays, OCR is capable of recognizing and extracting text from a wide variety of sources, including printed documents, invoices, forms, passports, and identification cards, among others. In fact, there are various online tools that can be used for free for this purpose, such as Online OCR or pdf24.

And why do we want to talk about this? OCR technology has proven to be particularly useful in identity verification. By using OCR, it’s possible to scan and extract relevant information from identification documents such as passports, driver’s licenses, or ID cards. This streamlines the verification process, as the information can be automatically read and compared with existing databases, thereby improving the efficiency and accuracy of identity verification.

How Does OCR Technology Work?

As we’ve hinted at earlier, this technology relies on a series of steps and algorithms to recognize and convert printed or handwritten text into editable digital data. 

But how does it work exactly? Here are some fundamental steps of its operation:

  • Image acquisition: The first step in the OCR process is to acquire an image of the document to be processed. This can be done using a scanner or a digital camera. The quality of the image is crucial for obtaining accurate results, as a clear and sharp image facilitates character extraction.
  • Image preprocessing: Once the image has been acquired, preprocessing is performed to enhance its quality and facilitate character detection. At this stage, techniques such as contrast correction, noise removal, image straightening, and region of interest segmentation can be applied.
  • Character detection: After preprocessing, character detection is carried out on the image. This involves identifying regions containing text and separating these regions from the rest of the image. Edge detection and image segmentation algorithms are used to achieve this.
  • Character segmentation: Once text regions have been identified, the next step is to segment individual characters. This involves dividing words or lines into separate characters. Techniques such as text structure analysis and character pattern recognition can be used in this process.
  • Character recognition: When characters have been segmented, recognition of each character is performed. Different approaches to character recognition exist, such as template-based recognition, statistical recognition, and machine learning-based recognition.
  • Post-processing and error correction: After character recognition, post-processing is performed to correct any errors. Techniques such as comparison with dictionaries, spelling error correction, and contextual coherence detection can be used.
  • Conversion to digital format: Once character recognition and correction have been completed, the text is converted into a readable and editable digital format, such as plain text or structured format like XML or PDF.

What is OCR Used For? All Applications

OCR has a wide range of applications in various fields, such as:

  • Identity verification: This technique is fundamental in these processes, as it allows for the extraction of relevant information from identification documents, such as passports, ID cards, or driver’s licenses. By scanning these documents, OCR can automatically read data such as names, birthdates, and identification numbers and compare them with existing databases to verify authenticity and identity matching.
  • Form automation: OCR is widely used to automate form processing. Instead of manually entering information from forms into a database, OCR can automatically extract data from handwritten or printed fields and convert them into digital text. This saves time and reduces errors in tasks such as medical record management, survey data collection, and job application processing.
  • Invoice and receipt recognition: This tool allows for the automatic extraction of key information, such as supplier name, date, amounts, and invoice numbers, from scanned documents or photographs of receipts. This facilitates accounting and expense tracking, as well as efficient management of financial information in businesses.
  • Accessibility and document digitization: OCR plays a crucial role in the accessibility and digitization of printed documents. It enables the conversion of books, newspapers, and physical documents into digital format, making storage, search, and distribution easier. Additionally, OCR is used to create accessible e-books for visually impaired individuals, as it can convert printed text into synthesized speech or Braille.
  • Automatic translation: By extracting text from documents in a given language, OCR allows automatic translation systems to efficiently convert it into another language. This is especially useful in translating legal, technical, or scientific documents, where accuracy and speed are crucial.
  • Barcode and QR code recognition: OCR is used in reading barcodes and QR codes in various industries. It enables automatic extraction of encoded information such as product numbers, prices, or links to websites. This facilitates inventory tracking, payment processing, and interaction with digital content associated with the codes.
  • Security and fraud prevention: This technique is used to enhance security and prevent fraud in various contexts, such as detecting forged identification documents by identifying discrepancies, inconsistencies, or signs of manipulation in the information, or it’s also implemented to read and verify characters printed on checks and other financial documents to detect alterations or attempted counterfeiting on checks, strengthening security and preventing fraud in monetary transactions.
  • Privacy protection and personal data: By automating identity verification through OCR, the exposure of personal data to human errors or malpractices is minimized. By reducing the need for manual intervention, privacy protection is enhanced, and risks associated with inappropriate manipulation of personal information are reduced.

What are the advantages and benefits of OCR in identity verification?

Finally, we’re ready to tell you about the advantages and benefits of this technique: well, OCR offers numerous advantages and benefits in various areas, especially in identity verification such as:

  1. Automation and time-saving: Instead of having to manually enter data from identity documents, forms, or invoices, OCR can automatically read and recognize text, significantly speeding up the process. This saves time and allows employees to focus on more strategic and high-value tasks.
  2. Improved accuracy: Human errors in data entry can be common, especially when dealing with large volumes of data. OCR drastically reduces the possibility of typographical or interpretational errors, resulting in higher accuracy and reliability in identity verification and other related tasks.
  3. Efficiency in document processing: The ability to automatically extract data from scanned documents or photographs speeds up workflows and reduces the need for human intervention in repetitive and laborious tasks. This leads to greater operational efficiency and resource savings.
  4. Enhanced user experience: Customers and users can provide physical or digital documents, and OCR takes care of extracting and verifying the necessary data quickly and accurately. This reduces administrative burden for users and improves customer satisfaction by accelerating and simplifying processes.
  5. Increased security and fraud prevention: By automating the reading and verification of identification documents, OCR allows for quick and accurate comparison of data with existing databases. This helps detect forged or manipulated documents. As a result, security is strengthened, and risks associated with identity verification are reduced.
  6. Access to digitized information: Facilitates storage, search, and access to information, thereby improving document management and reducing reliance on physical files. Document digitization also contributes to the long-term preservation and protection of information.

At Silt, we use OCR technology developed directly by ourselves: this allows us to be much faster and more flexible in the types of documents we accept, and, above all, this is why we can offer a better price to our customers.

Interested? Create your free account and book a free demo with us. Start verifying your users today with the least friction possible.