In this article, we will explore exactly what OCR document classification is, how it works and some of its benefits. Read on to learn more.
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OCR document classification is the process of using Optical Character Recognition (OCR) technology to read and categorize documents based on their content. It helps sort files like invoices, receipts, or forms into specific groups automatically, making organization and retrieval much easier.
Example: OCR document classification can be used to sort scanned invoices from vendors like "ABC Supplies" with product numbers like 12345 into a folder for office equipment, while categorizing receipts for items like "XYZ Widget Pro" into a separate folder for electronics.
Here are some of the benefits of using OCR document classification:
OCR document classification saves time by automatically identifying and organizing documents into predefined categories. This reduces manual sorting, improving efficiency and freeing employees for other tasks.
By minimizing manual input, OCR reduces the risk of errors in document classification. This ensures critical data is stored correctly and can be accessed quickly when needed.
Classified documents are easier to track and retrieve, speeding up workflows. Teams can focus on decision-making instead of spending time searching for misplaced files.
As document volume increases, OCR can handle larger workloads without additional effort. It adapts to growing data needs, making it a long-term solution for expanding businesses.
By automating labor-intensive tasks, OCR helps lower administrative costs. Businesses can redirect resources to areas that drive growth and profitability.
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Use our 10-step OCR document classification process to efficiently sort your files.
The process begins by converting a physical or digital document into an image format, such as PDF or JPEG, for analysis. High-quality scans ensure better accuracy in the subsequent steps.
Example: A physical receipt from "TechMart" for a "Laptop X200" is scanned into a high-resolution PDF using a multifunction printer.
OCR software reads the scanned image and extracts the text from it by identifying characters and words. This converts the image into a machine-readable format like plain text or structured data.
Example: The OCR tool recognizes "Invoice #56789" and "Product: Printer Z45" from the scanned PDF and converts them into editable text.
The extracted text is cleaned and formatted to improve accuracy. This may involve removing noise, correcting skewed text, or standardizing fonts and layouts.
Example: OCR preprocessing corrects a blurred entry of "Deskmp Pro" to "DeskLamp Pro" in a product catalog PDF.
The system identifies specific data fields like invoice numbers, dates, or product descriptions based on predefined templates or patterns. This step ensures relevant information is captured accurately.
Example: The software pinpoints "Order ID: 89234" and "Item: Monitor A300" on an e-commerce receipt and tags them for classification.
The extracted data is compared against a set of predefined rules or categories to determine where the document belongs. This ensures each document is classified consistently.
Example: A document mentioning "ABC Office Supplies" and "DeskChair DX100" is categorized under "Furniture and Fixtures."
The document is saved in its appropriate folder or database category based on the classification result. This ensures it is easy to retrieve later.
Example: The invoice for "Product X12" is automatically filed under "Invoices > Electronics."
A final check is performed, either manually or automatically, to ensure the classification is accurate. Any errors can be corrected before storing the document permanently.
Example: A quality control step flags a misfiled "Printer Z45" receipt in the "Stationery" category, prompting correction to "Electronics."
The classified data is integrated into systems like CRMs, ERPs, or databases for further use. This allows for seamless data sharing and business insights.
Example: The details of "Order #99876" for "Scanner Q900" are synced into the company's inventory management system.
Documents are indexed using keywords, making them searchable for future needs. This simplifies accessing specific files quickly.
Example: Searching "Printer Z45" in the document management system instantly pulls up all related receipts and warranties.
Feedback from errors or new document types is used to refine classification rules and improve accuracy over time. This ensures the system stays effective as needs evolve.
Example: The system learns to recognize a new product line, "Tablet G7," and adjusts its categories to include it under "Electronics."
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TechEase Solutions, a growing IT services provider, faced challenges organizing invoices, contracts, and purchase orders. They implemented our 10-step OCR document classification process to simplify file management and improve efficiency.
TechEase converted physical and digital documents into high-resolution PDFs and images for processing. For example, a client invoice for "Laptop X100" was scanned as a PDF.
OCR software read the images and converted the text into a machine-readable format. It accurately captured details like "Invoice #23456" and "Client: DataCore Inc."
The extracted text was corrected for errors like blurry characters or misaligned text. For instance, a misspelled "Servevr Pro" was corrected to "Server Pro."
The system identified specific fields, such as invoice numbers, client names, and dates, using set templates. It pinpointed details like "Order ID: 33456" and "Date: 12/15/2024."
Each document was assigned to a relevant category based on the extracted data. For example, a document referencing "Supplier: OfficeMart" and "Item: DeskChair DX50" was classified as "Office Supplies."
The documents were stored in well-defined folders for easy access. For instance, the invoice for "Server Pro" was placed under "Invoices > Hardware."
A quality control check ensured documents were placed in the correct categories. For example, a receipt for "Printer Z90" originally misfiled under "Stationery" was corrected to "Electronics."
The organized data was integrated into TechEase’s ERP and CRM platforms. For instance, "Invoice #33456" was automatically added to the accounting system.
Keywords were indexed, allowing team members to quickly search for specific documents. Searching "Server Pro" instantly retrieved all relevant invoices and records.
Feedback and new document types were used to refine classification rules and boost accuracy. For example, the system learned to recognize files from a new supplier, "TechSupply Co."
We hope you now have a better understanding of how OCR document classification works and its benefits. If you enjoyed this article, you might also like our article on invoice discounting vs factoring or our article on OCR model.