In this article, we will explore exactly what OCR Software for price tag is and its common benefits. We also share our simple 8 step process for using price tag OCR software. Read on to learn more.
Price Tag OCR (Optical Character Recognition) is a technology that scans and converts printed or handwritten price tags into editable and searchable digital data. It automates the process of entering price information into a system, enhancing accuracy and efficiency.
Example: Using Adobe Acrobat's OCR technology, a company can scan paper invoices from vendors like Office Depot and extract key details such as invoice number 12345 and total amount $567.89 for seamless digital record-keeping.
Here are some of the most common benefits of using OCR software for price tags:
Using OCR software for price tag reading significantly speeds up data entry processes. It removes manual input for instant inventory updates and faster checkout times at stores.
OCR technology reduces human errors associated with manual data entry. It captures price information as it appears on tags and improves reliability in pricing and inventory management.
Automating the process of price tag reading with OCR software reduces labor costs and the need for extensive training. Businesses can allocate resources more efficiently, leading to overall cost reductions.
Quick and accurate price scanning helps in maintaining correct pricing, thus preventing checkout delays and pricing disputes. This leads to a smoother shopping experience and higher customer satisfaction.
OCR software can be easily integrated with existing retail management systems. This flexibility allows for seamless updates to pricing and inventory without the need for significant system overhauls.
OCR solutions can be scaled according to business needs, handling everything from small retail operations to large-scale enterprises. This adaptability makes it a viable option for businesses of all sizes.
Here’s how to implement our OCR process for price tag reading:
Capture the image of the price tag using a camera or scanner to ensure high resolution and clear visibility of text.
Example: A high-resolution photo of a price tag on a "Samsung Galaxy S22" priced at $799 is captured using a smartphone camera to ensure all text is readable.
Enhance the image quality to improve OCR accuracy. This can include adjusting brightness, contrast, and sharpness.
Example: The image of the "Apple MacBook Air" price tag at $999 is adjusted for brightness and contrast to highlight the price and product name against a light background.
Use OCR technology to identify and localize text regions within the image.
Example: OCR software scans the image of a "Sony Headphones WH-1000XM4" priced at $349, detecting and isolating the area where the price and product name are displayed.
Convert the detected text regions into machine-encoded text using OCR algorithms.
Example: The software recognizes the characters ‘$249’ and 'Nintendo Switch Console' from the price tag image, converting them into editable text.
Extract relevant information such as product name and price from the recognized text.
Example: From the recognized text, the software extracts the product name "Fitbit Versa 3" and the price "$229" for further processing.
Verify the extracted data against predefined rules or databases to ensure accuracy.
Example: The system checks the extracted price "$59" for "Logitech Mouse" against an inventory database to validate its correctness.
Format the data into a structured form suitable for integration into business systems.
Example: The price and product name "Canon EOS 1500D at $449" are formatted into JSON format for easy integration into the retail store’s inventory management system.
Store the processed data in a database or other storage system for future reference or analysis.
Example: The validated and formatted details of the "Dyson V11 Vacuum Cleaner priced at $599" are saved in the sales database for tracking and future sales analysis.
TechWare Solutions is a renowned electronics retailer, known for its wide range of cutting-edge products. Here's how they implemented our OCR software process for price tags to enhance inventory management and pricing accuracy.
Collect images of price tags from over 500 electronic items, including the latest smartphones and laptops, using high-resolution cameras to ensure all text is legible for processing.
Adjust brightness and contrast settings on 450 captured images to enhance clarity, focusing specifically on making the price details stand out to facilitate more accurate OCR results.
Utilize OCR technology to scan and isolate text regions on 350 price tags from electronic goods, ensuring the product names and prices are correctly identified for text recognition.
Process text from 300 price tag images, converting them into editable formats to extract critical pricing and product data such as "iPad Pro 11-inch for $799".
From the recognized text, automatically extract the product name and price for 250 items, such as pulling “$1200” and “Sony 4K Ultra HD TV” to prepare for data validation.
Cross-verify the extracted pricing information of 200 products against TechWare’s central pricing database to ensure accuracy, catching any discrepancies such as incorrect prices or mislabeled products.
Format the validated data from 150 product tags into TechWare’s inventory system specifications, such as converting details into SQL entries for immediate update of the inventory records.
Securely store the processed data from 100 updated price tags in the company’s database, enabling real-time inventory tracking and facilitating accurate price updates across all store locations.
We hope that you now have a better understanding of what OCR software for price tags is and how it works. If you enjoyed this article, you might also like our article on ICR vs OCR or our article on OCR for accounting.