The most innovative approach to document processing was, at one time, optical character recognition (OCR). It allowed teams to copy and paste text from document image files, completely revolutionizing their document processing workflows. However, OCR only scratches the surface of the possibilities offered by document digitization in the age of AI and digital transformations.
Scanned documents are converted into searchable and editable digital files using OCR technology. This uses shape recognition algorithms to extract text from scanned documents or images. OCR technology is developing to recognize text accurately and successfully.
In this article, we will describe the what and how of this document scanning process. Let's start by describing OCR in more detail.
What is OCR?
OCR, as stated in the introduction, is essentially a text recognition technology. This text extraction can help extract text from various sources, such as photographs, newspapers, and scanning of handwritten documents. OCR analyzes documents to produce accurate conversion results. This includes pre-processing, conversion and post-processing. Character segmentation and other methods help ensure that the text and image match.
What is document scanning and how does it work with OCR?
Document digitization, as it is called, is the process of transforming physical documents into digital documents to enable virtual storage, collection and processing. Almost all stages of the document lifecycle, including import, categorization, data labeling, data review and data export, are now included in document digitization.
Teams can copy, paste, and reuse text that appears on scanned or imaged documents for other purposes after it has been converted by OCR into selectable and editable characters. OCR is a powerful tool for document scanning because it allows teams to copy and paste document data into databases instead of having to type it again.
Role of OCR in document scanning
The possibilities for using and organizing information have never been so numerous thanks to digitalization. OCR software such as JPG to text analyzes the visual characteristics of characters, such as shape, size and pattern, to recognize them and convert them into machine-coded text. The result can be stored, edited, searched and shared electronically, allowing seamless integration into digital systems.
Improved search possibilities
OCR technology helps index documents and make them searchable, eliminating the need for manual scanning or tedious navigation. Users can quickly locate specific information within a document or large database, improving productivity and saving valuable time.
Increased accessibility
OCR allows people with visual impairments or reading difficulties to access and understand text by converting physical documents into digital formats. Converted documents can be read aloud using text-to-speech technologies or displayed with larger fonts, promoting inclusion and equal access to information.
Efficient data extraction
OCR facilitates the automated extraction of relevant data from documents, eliminating the need for manual data entry. For example, invoices, forms or receipts can be processed and the extracted data can be directly integrated into databases or accounting systems. This helps reduce errors, speed up workflows, and improve overall data accuracy.
Space and cost savings
Physically storing documents can be cumbersome and require considerable space and organizational effort. Scanning documents using OCR eliminates the need for significant physical storage, reducing costs associated with printing, archiving and searching. It also minimizes the risk of losing documents due to them being damaged or misplaced.
OCR Applications
As OCR advances, it is expected to find even more innovative applications, transforming the way we interact with and manage textual information.
Archiving documents
OCR plays a crucial role in the preservation and digitization of historical documents, books and manuscripts. Many invaluable texts and documents are stored in physical form and are subject to deterioration over time. These documents can be converted to digital format, ensuring their longevity and accessibility for future generations. OCR captures the text and structure of documents, making them easy to find and retain while minimizing the risk of damage or loss. This application is particularly valuable for libraries, museums and archival institutions that aim to safeguard cultural heritage.
Document recognition and sorting
OCR technology allows you to automatically recognize and classify different types of documents based on their content. Invoices, contracts, passports and any other type of document commonly used in businesses can all be recognized and classified by OCR algorithms. This automated recognition and sorting process helps streamline document management workflows, resulting in increased efficiency and productivity. For example, in a large-scale administrative process, OCR can accurately classify incoming documents and route them to the appropriate departments or individuals for further processing. It is particularly useful in industries such as healthcare, finance and law, where the volume of documents can be considerable.
Extracting content from images
OCR technology is not limited to scanned documents, it also allows you to extract text from images or screenshots. With this capability, visual content information can be processed and analyzed efficiently. For example, social media platforms generate large amounts of image-based content such as memes, infographics, or product screenshots. OCR can extract text from these images and transform it into editable and searchable formats. This simplifies interpretation, translation or data extraction. Content creators, marketers, and researchers can benefit from this application by quickly extracting valuable information from visual sources.
Language translation
The integration of OCR with translation tools opens up new possibilities for multilingual communication and understanding. OCR technology can convert printed or handwritten text in one language into another, making it easier to overcome language barriers and facilitate communication between individuals or organizations. For example, a traveler in a foreign country can use translation apps with OCR technology to capture and translate signs, menus, or documents in real time.
Likewise, businesses operating in international markets can leverage OCR and translation tools to process and understand documents written in different languages, thereby improving their efficiency and accuracy in global operations.
Conclusion
OCR is beneficial in many circumstances, but it is particularly useful when scanning documents. It saves a ton of resources and provides precise and accurate results. Document scanning is modified by technology by transforming images into searchable and editable text. Precise data extraction from inaccessible files enables widespread industrial application.