Can Deep Learning and AI Help in Preprocessing Images for OCR?

Anusha Venkatesh
IDP Evangelist

Deep learning is an emerging subset of artificial intelligence in which systems are developed to learn from observation and make decisions without human intervention.

Deep learning systems seek logical patterns in unstructured and uncategorized data sets and, as we saw in How Artificial Intelligence And Deep Learning Algorithms Deliver OCR Accuracy for Business, has powerful applications in optical character recognition (OCR) conversions.

OCR Quiz:

OCR Quiz: 
ocr quiz-1


Hey OCR which one of these is a “3”? 
It is easy for you and me to understand each of these images is a “3.”  

But an OCR would fail this quiz.
Can DL help an OCR? This video walks you through how DL works.

By mimicking the human brain’s recognition and recall faculties, deep learning technology enhances the accuracy of OCR conversions and helps generate insights from the extracted text.

Let’s now look at the conversion process more closely, and specifically see how deep learning helps in the preprocessing of images.

OCR vs. OCR+ML vs. IDP

OCR has inherent limitations when used to extract data from unstructured documents and images.  The addition of ML as a preprocessing step helps, but is not sufficient. A better approach is termed Intelligent Data Processing (IDP) which is a template-free, AI-driven approach that is well suited to complex document extraction.

OCR Technology

OCR technology has been in use for a long time to extract text from scanned documents and images to an editable, machine-readable form.  The output scanned document is a file that you can edit in Word, not a jpg.

This text recognition delivers significant savings of time, effort, and cost over manual reading and data entry. Many OCR applications today include add-on functionality to recognize some page attributes such as simple tabular structures, fonts, and paragraph styles.

How does OCR work?

The image to be extracted is presented to the final step using a well-defined template.  The template tells the OCR to extract the data in a particular, stationary location on the document. Through this process, OCR converts an image into text.

The Importance of Image Quality in OCR Extraction

The success and accuracy of OCR conversion systems are a function of the algorithm used, the quality of the image, and other considerations. While OCR engines are very mature and stable technology, we also need technologies that can improve the quality of images to yield better OCR results.

Images we want to process may have a range of problems such as:

  • Image is blurred
  • Image lacks contrast
  • Scan is skewed
  • Scan is warped
  • Scan is fuzzy
  • Text not aligned in the original document
  • itself could have text that is not properly aligned
  • Page background may be smudged or muddled
  • And more

Such image imperfections will introduce errors in the conversion process and lead to a loss of accuracy.

For this reason, image preprocessing is an extremely important part of the process.

Traditionally, some preprocessing was done manually, prior to attempting the OCR step. Then rules-based software applications that had the ability to do some preprocessing became available.

Now we see deep learning applications being used to handle image preprocessing.

What is OCR Preprocessing?

Image preprocessing works to normalize the content and exclude variations that would reduce the likelihood of text recognition. The steps in preprocessing could include:

Frequently asked questions

What does your pricing model look like?

We price based on the annual volume of pages and complexity of document type.  We can get you preliminary pricing once we outlined a solution.  Let's do this.

To know more, book a 15-min session with an IDP expert

How can I try Infrrd before I commit to a full deployment?

Sure.  The first step is to schedule a guided demo where you get to jump into the thick of it.  After you explore our solution you can try a proof of concept. When you're ready, you can deploy the system to one use case.  Then more use cases.  Then across your enterprise.

To know more, book a 15-min session with an IDP expert

How does your system integrate with others in my enterprise?

We play nice.  Our solutions are API-based.  Your documents are feed into the solution using APIs. And extracted data is sent out through APIs.  We use REST APIs.

To know more, book a 15-min session with an IDP expert

Does your solution run in the cloud or on premise?

Our solution is cloud-native but is also design for premise deployments.  Your choice on how you want to deploy it.

To know more, book a 15-min session with an IDP expert

Does Infrrd run on mobile or desktop device?

Glad you asked.  Our data extraction process runs on servers.  We have found performance and accuracy decline when running on a desktop or mobile device. (Remember Infrrd is running a powerful AI stack).

To know more, book a 15-min session with an IDP expert

Does your system work out of the box or does it require training?

Common documents and use cases work out of the box.  The cool thing is your solution will improve as the system learns from your documents upfront and over time.

To know more, book a 15-min session with an IDP expert

How does your solution handle corrections?

Did you know no system is 100% accurate all the time?  When extraction errors occur you want to correct them.  We provide a simple UI that your business analyst will use to make corrections.

To know more, book a 15-min session with an IDP expert

Does your solution work with handwriting?

Our solution excels at data extraction from handwriting.  We've got proprietary methods and techniques that do the trick.  It's pretty cool.  See for yourself.

To know more, book a 15-min session with an IDP expert