How to extract data from tables inside a scanned PDF or image

One of the many use cases of OCR is to extract data from images of tables - like the one you find in a scanned PDF. Other document types like receipts, invoices, contracts and more also follow the same layout and also benefit from our table OCR feature. For all these documents we recommend that you enable check the Receipt scanning and/or table recognition option on the front page. If you use the OCR API, you get the same result by turning on the table OCR mode. The result is that the OCR'ed text is sorted line by line - just like you find it in the table. This makes the OCR API the perfect receipt capture SDK.

Table Parsing Example

The screenshot below shows the OCR result of an image of a table scan, in this case from a Chinese text book. With the table OCR mode active, the structure of the text output is the same as on in the table.

Table OCR Parsing OCR Text Result
We highlighted a few lines in yellow to visually help you to compare the left input image and the extracted OCR table data on the right.


In the OCR API the isTable = true switch triggers the table scanning logic. More details are available in the table OCR flag section of the OCR API documentation

Test Table OCR

You can test table parsing and data extraction directly on our front page. Here is the original table textbook scan. In this case the selected OCR language is Chinese:

Online OCR for Tables
The link to the table image is - just paste it into the URL box on the front page.

View OCR API Performance
Follow OCR API on Twitter
Free RPA Software
Copyfish OCR Browser Extension
Selenium IDE
Try UI.Vision RPA, our OCR-powered Robotic Process Automation (RPA) software. It is available as free browser extension as RPA Chrome and RPA Firefox (OSI-certified Open-Source) plus computer-vision extension modules. UI.Vision RPA is fun to use - and its OCR screen scraping features are powered by the OCR API.

Do you have an OCR API question? Please email us or visit the OCR API Forum - we love to answer OCR questions.