Technology helps OCR process in detecting the letters and converts them into words and phrases that are actionable, i.e. searchable and editable format. It is essential in business workflows that involve print media, as it enables the conversion of paper documents into searchable and editable text data. Similarly, businesses have to deal with vast amounts of paperwork, from invoices and contracts to forms and receipts. Converting these paper documents into searchable and editable text data is crucial for streamlining operations and improving productivity. This article will explore the significance of OCR, its working mechanism, types, and the numerous benefits it offers. By leveraging OCR solutions, businesses can unlock the potential of their document management system and make data-driven decisions.
What is Optical Character Recognition (OCR)?
This character recognition technology converts image text into readable and editable text formats. It enables businesses to extract valuable data from printed documents, making it accessible for further analysis and processing. By utilizing OCR, the text within images becomes searchable, editable, and compatible with various software applications.
How OCR Work?
OCR extraction employ a series of steps to convert image text into actionable data:
1. Image Acquisition:
OCR scanner app scans documents and converts them into binary data, where light areas are classified as the background and dark areas as text.
2. Preprocessing:
The OCR software cleans the image by removing errors and enhancing its quality. This includes deskewing to fix alignment issues, despeckling to remove digital image spots, and cleaning up boxes and lines.
3. Text Recognition:
OCR algorithms use either pattern matching or feature extraction techniques for text recognition. Pattern matching compares characters in the scanned image with stored templates, while feature extraction analyzes image attributes like lines, loops, and intersections to identify the best match.
4. Postprocessing:
After analyzing the text, the OCR system converts the extracted data into a computerized file format. Some OCR systems can generate annotated PDF files that include both the original scanned image and the recognized text.
Types of OCR
There are different types of OCR technologies based on their applications and capabilities:
1. Simple OCR:
This type uses pattern-matching algorithms to compare text images with stored templates. It works well with documents typed in known fonts but has limitations when dealing with various font styles and handwriting.
2. Intelligent Character Recognition (ICR):
Modern OCR systems employ ICR technology, which identifies human reading behavior. Using machine learning and neural networks, ICR analyzes text at multiple levels, looking for image attributes like curves, lines, and intersections. This allows quick and more accurate recognition of text characters in the image.
3. Intelligent Word Recognition:
Similar to ICR, this type processes entire word images instead of individual characters. It combines the principles of ICR with word-level analysis for improved recognition accuracy.
4. Optical Mark Recognition:
This type focuses on identifying logos, watermarks, and other text symbols in a document, making it useful for tasks like data extraction from surveys or questionnaires.
Benefits of Optical Character Recognition
OCR technology offers numerous benefits for businesses:
1. Searchable Text:
By converting image text into searchable data, OCR enables businesses to create fully searchable knowledge archives. This process allows for quick and efficient storage of information resulting in saving time and effort in manual document sorting.
2. Operational Efficiency:
OCR software integrates document workflows with digital processes, automating tasks such as form verification, reviews, and editing. It eliminates the need for manual data entry by scanning hand-filled forms and converting handwritten notes into editable texts. This boosts efficiency and reduces errors in document processing.
3. Improved Decision-Making:
OCR is often part of broader artificial intelligence solutions, enabling businesses to extract valuable insights from scanned documents. For example, optical character recognition technology can identify brand logos in social media posts or analyze product packaging in advertising images. These AI-powered solutions help businesses make informed decisions, reduce expenses, and enhance the customer experience.
4. Cost and Space Savings:
By digitizing paper documents through OCR, businesses can reduce physical storage requirements and associated costs. Digital files are easier to manage, organize, and share, leading to significant savings in physical space and resources.
Conclusion
OCR technology has revolutionized the way businesses handle paper documents, enabling the conversion of image text into actionable data. By leveraging the power of OCR solutions, businesses can enhance operational efficiency, improve decision-making, and unlock the full potential of their document management system. Embracing OCR is a step towards a more streamlined and data-driven future for businesses.
