Understanding OCR Technology and How Document Scanning Works

OCR, short for Optical character recognition, is a technology that businesses use for automating the process of data extraction from written or printed text. By converting hand-written data or printed text from a scanned document or an image into a machine-readable format, businesses are able to enhance data processing activities such as searching and editing.

The OCR Process

To understand how OCR works, take a look at the following steps through which document scanning is enhanced:

Step 1: Image Pre-processing

In the first step, an OCR technology software scans images to preprocess them. This is done in the following ways: 

  • De-skew and Despeckle

The documents are properly aligned in this method. Any unwanted spots and crumpled/folded edges are smoothened. Additionally, the document can also be tilted in either direction to make it more readable. 

  • Binarisation

Colored images are converted into binary images, such as in grey-scale. This is essential as OCR scanners are based on algorithms that require binary images for data processing. 

  • Layout Analysis and Line Removal

In this method, textual data present in columns, blocks, or paragraphs are recognized while non-glyph lines and boxes are filtered out. This process involves the recognition of texts and data by identifying columns, paragraphs, and distinct blocks. Furthermore, non-glyph boxes and lines are filtered out for more clarity. 

  • Script Recognition

In the case multilingual documents are provided for data extraction, the script recognition method is used to identify ad classify different fonts, styles, and the language used in the document. 

  • Character Isolation

Segmentation, or character isolation, divides a document present in the form of an image file into different characters. If the document includes textual data, OCR segmentation is carried out at the character level. 

Step 2: Character Recognition

Character recognition works in the following two ways:

  • Pattern Recognition

This method is commonly used for typewritten documents. By utilizing the “Matrix Matching” algorithm, different patterns in the text are identified to enable pixel-by-pixel comparison between an image and a stored glyph. 

  • Feature Extraction

This technique uses the “k-nearest neighbor” algorithm that helps in the classification of distinct components of a particular letter or alphabet. For example, the textual data is converted in the form of particular lines, loops, and their directions to enable the detection of unique characters such as the difference between the alphabet U and V. 

Step 3: Automated Form Population

The final step involves the automated data entry process. In this stage, the preprocessed data is added into respective fields of a verification form to save the company’s and the end-user’s time. 

How Does OCR Technology Enhance Data Accessibility? 

A popular application of OCR software is the automated transformation of a PDF or JPG file into a text-based machine-readable format. Files that are processed through OCR technology, such as bank statements, ID cards, passports, receipts, contractual forms, invoices, etc. become:

  • Searchable from a larger database to identify the correct document within seconds
  • Easily viewable,  with an option to search particular words present in each document
  • Editable in case corrections have to be made

The Benefits of Data Extraction Through OCR Technology

Companies that use OCR technology for the conversion of paper-based scanned images and PDF files save both time and resources that otherwise would have been required for editing or searching a vast amount of data. Once processed, textual data can be used for numerous purposes, making business operations more efficient and manageable. 

To name a few, the benefits of OCR technology are listed below: 

  • Eliminates the need for manual data entry processing
  • Cost reduction, as labor costs can be substantially reduced as automated processes are rapid and require fewer resources
  • Automated data extraction is less error-prone than its traditional counterpart 
  • Eliminates the business’s requirement of a physical storage space that can then be used for other purposes
  • It ultimately improves the business’s productivity by making daily processes more efficient and convenient

Should Companies Invest In Ocr Software? 

Robust data extraction solutions such as OCR software have the ability to manage multilingual documents. The AI-powered software can process textual data from both digital and paper-based documents. This eliminates the need for physical storage space and substantially reduces manual data entry and processes. 

By integrating OCR technology in their systems, companies can:

  • Minimize costs
  • Expedite business processes
  • Automate data processing
  • Secure the data in a centralized database, reducing the chances of theft and loss of documents during break-ins or fires
  • Enhance employee productivity by providing them with up-to-date software.
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Aniket jain

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