Image Quality Enhancement – A Vital Data Processing Technology Deciding The Quality of Output Data

In DIGI-TEXX’s data processing operation, especially when it comes to processing our client’s Historical Documents from the 14th century,  the quality of the pre-processed images is one of our challenges and top priority.

Digitizing historical documents is an urgent action since these documents will eventually vanish as they are either printed or written on ordinary paper, which has a limited lifespan and will decompose over time. Even the captured images of these documents usually come in bad status (bad light and color, incorrect angles, and so on).

Indeed the extraction engine is like our human eyes. The better the image quality, the faster our eyes can see and process. So when the input document is clear, the output data speed and automation rate will be increased.

DIGI-TEXX applies Image Quality Enhancement technology in the pre-processing step to transform the images and make them more suitable for OCR engines and machine vision algorithms in later processing stages. 

This technology will identify the key features and details of the images, then adjust them using professional digital image processing techniques like:

  •  Remove image background noise
  •  Adjust skew and rotation
  •  Crop the excess areas
  • Tune the brightness, sharpness, and other color settings

At DIGI-TEXX, we focus on analyzing how a good and bad image decides the accuracy and automation rate of the data processing process. This step is crucial because it determines whether human assistance is required or not and how fast a document can proceed.

Image Quality Enhancement is applied to DIGI-XTRACT – an intelligent data extraction engine developed by DIGI-TEXX powered by our cutting-edge technologies like Machine Learning, Natural Language Processing, and Deep Learning. 

It enables businesses to: 

  • Utilize and digitize thousands of valuable historical/old documents. 
  • Generate better input images for OCR engines and machine vision algorithms to enhance the straight-through process.
  • Enhance user experience as they don’t have to keep recapturing/rescanning the image.
  • Save employees from handling repetitive tasks.

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