The conventional way of working in the company is tedious, lacking accuracy and reliability in data. That’s the reason why companies are moving towards AI tools. These tools such as Optical Character Recognition(OCR) prove to be valuable in extracting valuable information from handwritten documents.
Now detecting and extracting text from images through OCR is easy and it will provide accurate and reliable results.
What Is Optical Character Recognition(OCR)?
OCR recognition is a technology that transforms handwritten or printed data into machine-encoded text. It’s become a crucial tool in the digital age that has various use cases in multiple industries.
OCR has the potential to examine and extract valuable information from images. For example, if anyone wants to scan a receipt or a form, online software scans the file and saves it with an image file name.
There is no need to use a text editor for research, editing and word count purposes. This blog will cover one of the most important OCR technology use cases.
Working of Optical Character Recognition(OCR)
The OCR recognition works in the following ways:
1. Image Acquisition
It can read documents easily and convert them to binary data or machine-readable text. OCR software can easily analyse the scanned images and categorises the light areas as background and dark as text.
2. Pre-Processing
OCR recognition removes errors and cleans the image to prepare it for reading purposes.
3. Text Recognition
The two major kinds of OCR algorithms or software processors that it uses for text recognition are:
4. Pattern Matching
The process of isolating a character image is known as a glyph. Pattern recognition works where the stored glyph has the same scale and fonts as the input glyph.
5. Feature Extraction
Feature extraction breaks down the glyph into features like closed loops, lines, line intersections and directions. Moreover, this software then uses these features to find the appropriate match among its various stored glyphs.
6. Post-processing
After analysing the system has the potential to convert the extracted data into a machine-readable format. Many OCR recognition software can generate annotated PDF files that cover both versions of the scanned documents i.e., after and before.
Use Case: Document Digitisation
The most typical use of OCR recognition is document digitisation. Thanks to technological advancements there is a considerable transformation from physical to digital documents. OCR recognition has the potential to convert paper-based physical documents into digital ones that make it convenient to store, explore and share pieces of information.
1. Improves Efficiency
OCR recognition has the potential to make document digitisation less time-consuming and more efficient. Before the arrival of OCR recognition, manual data entry was the only suitable option for document digitisation. This procedure was slow and error-prone; that’s why OCR has made it possible to transform huge data into digital one within a short time period, saves time and improves efficiency.
2. Improved Accuracy
OCR recognition has the potential to increase the accuracy rate of document digitisation. The conventional way of entering data was error-prone, like misspellings, typos or omissions. While on the other hand, OCR technology uses advanced algorithms that have the potential to identify and extract data from images. It reduces the number of errors and makes it more reliable and accurate.
3. Cost-Effective
Document digitisation is now more cost-effective than ever before. Before OCR recognition, document digitisation was a manual procedure that required a considerable amount of resources. This technology omits the need for manual data entry which results in lowering labour costs.
Moreover, digitised documents are easy to retrieve and store which reduces the demand for physical storage space.
4. Improves Accessibility
OCR recognition has the potential to improve information accessibility. Now, companies can easily share and access digitised documents from anywhere and anytime. It is now convenient for people to access data that was previously unavailable like historical archives and records.
5. Improves Customer Service
OCR recognition improves customer relations with organisations by making it convenient for companies to process customer requests easily and by responding to their queries instantly. With OCR, companies can easily access consumer data and respond to customer requests in an efficient and timely manner, improving customer loyalty and satisfaction.
Key Takeaways
OCR recognition has transformed the way companies digitise documents. It improves accuracy, efficiency, accessibility and cost-effectiveness. It has become a crucial tool for multiple industries such as finance, education, government and healthcare.
Globally, OCR has become a crucial tool for many organisations and businesses because it has a broad range of applications. Thanks to the digital world that continues to evolve and plays a crucial role in document digitisation.
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