How to improve OCR Accuracy

2 min readFeb 28, 2024

In the digital era, mechanically transcribing text from scanned documents is impracticable for enterprises.

This is where OCR (Optical Character Recognition) systems come in: they automate the translation of photos into editable text, allowing for smooth data extraction.

What is OCR Accuracy?

OCR accuracy is an important indicator that measures how successfully software can convert printed or handwritten text from scanned pictures to digital format.

For example, when scanning a printed book into a digital text document, OCR accuracy determines how well the program catches each character and word from the scanned pages, ensuring that the resultant digital text closely resembles the original material’s structure and content.

How Does OCR Work?

OCR systems employ one of two algorithms to recognize the characters in the scanned document:

Pattern Recognition- The algorithm compares the characters in a document or picture to instances of supplied text.
Feature Recognition- Characters are recognized using characteristics of alphabets, arithmetic digits, or symbols such as angled lines, crossing lines, and curves.

How to Improve OCR Accuracy:

Improving OCR (Optical Character Recognition) accuracy is critical for producing more exact and consistent results when digitizing text from scanned photos or documents.

Here’s a step-by-step strategy to increasing OCR accuracy:

Step #1: Use High-Quality Source Images

Ensure source documents are scanned or captured in high resolution.
Use clean, well-lit, and well-aligned images to reduce noise.

Step #2: Optimize Image Resolution

Higher resolution images retain more detail and improve character recognition.
Aim for a minimum of 300 DPI (dots per inch) for printed text.

Step #3: Noise Removal:

Remove background noise, speckles, or artifacts that can interfere with OCR.
Image preprocessing techniques like thresholding or filtering can help.

Step #4: Enhance Image Contrast

Adjust contrast to make text stand out from the background.
This can help the OCR engine distinguish characters more effectively.

Step #5: De-skewing

Correct image skew or rotation, ensuring text is horizontal.
Skewed text can lead to misinterpretations by OCR.

Step #6: Choose the Right OCR Engine

Different OCR engines have varying strengths and weaknesses.
Experiment with multiple OCR engines to find one that suits your needs.

Why is KlearStack the Best OCR Engine for Your Business?

If your firm processes over 1000 documents per month and wants to achieve high OCR accuracy, look no further!

KlearStack is a sophisticated OCR solution. It stands out for its high recognition accuracy, cost reductions, and superior AI integration, making it a strong contender for efficient OCR solutions.

Here’s why KlearStack is the Best OCR Engine for Your Business:

Allows training for specific fonts or languages,
99% recognition accuracy.
Elimiates 70% costs
Leaverages Machine Learning and AI for 95% adaptive recognition
200% increase in productivity levels.
Instant set-up. No pre-requisite required