#Abbyy ocr tool how to
#Abbyy ocr tool free

We selected several documents-two easy to read reports, a receipt, an historical document, a legal filing with a lot of redaction, a filled in disclosure form, and a water damaged page-to run through the OCR engines we are most interested in.

#Abbyy ocr tool free

Some are quite expensive, some are free and open source. Some are easy to use, some require a bit of programming to make them work, some require a lot of programming. There are a lot of OCR options available. We couldn’t find single side by side comparison of the most accessible OCR options, so we ran a handful of documents through seven different tools, and compared the results.

We have been testing the components that already exist so we can prioritize our own efforts. One of our projects at Factful is to build tools that make state of the art machine learning and artificial intelligence accessible to investigative reporters. OCR, or optical character recognition, allows us to transform a scan or photograph of a letter or court filing into searchable, sortable text that we can analyze. Key-value pairs (interpreting the input as a form), as well as a CSV file.Do you need to pay a lot of money to get reliable OCR results? Is Google Cloud Vision actually better than Tesseract? Are any cutting edge neural network-based OCR engines worth the time investment of getting them set up? Using the browser interface, Textract outputs Our last candidate is also a paid cloud-based solution ( pricing).įor testing purposes, you can use Textract conveniently with the drag-and-drop browser interface, but for production-ready applications you will probably rather want to use the provided API. Note that there is also a Google Document Understanding AI beta version out now, which we haven't tested as of this point. Just as for Tesseract, based on this information one could try to detect tables, but again, this functionality is not built in. In fact, the original Cloud Vision output is a JSON file containing information about character positions. On the other hand, Google Cloud Vision doesn't handle tables very well: It extracts the text, but that's about it. However it is much better than Tesseract or ABBYY in recognizing handwriting, as the second result image shows: still far from perfect, but at least it got some things right. Google does well on the scanned email and recognizes the text in the smartphone-captured document similarly well as ABBYY. I'm going to use that option for our table image. Apart from the ones that are also provided by Tesseract, we can additionally ask ABBYY to output XLSX spreadsheets.

#Abbyy ocr tool how to

If you want to learn how to use the API, you'll find everything you need to know in these quick start guides.Īgain, we have different options with respect to the OCR output format. Unlike Tesseract, ABBYY Cloud OCR is not free ( pricing). This cloud service uses the ABBYY FineReader OCR engine, which can also be installed locally. I'm going to use the ABBYY Cloud OCR SDK API. ABBYY FineReaderĪBBYY offers a range of OCR-related products. Our blog posts about applying OCR to technical drawings and extracting dates from letters give an idea how. Of course you can process Tesseract's output by your own table extraction tool. It turns out that Tesseract outputs bounding boxes for areas of the image that contain text, but that doesn't even get close to proper table extraction. However, when it comes to the handwritten letter and the smartphone captured document, either nonsense or literally nothing is outputted.įor the output from the table image I used gImageReader, the GUI frontend mentioned above.

As you'll notice, Tesseract OCR recognizes the text in the well-scanned email pretty well.