The problem Document Quality Assessment solves

The problem statement aims to solve the issue of low-quality optical character recognition (OCR) data and poor document intelligence extraction caused by poor quality of text documents. The solution described in the problem statement aims to automatically determine the quality of these text documents before they undergo OCR and other processing methods, so that only high-quality documents are processed, reducing computational waste and increasing efficiency. This problem is particularly relevant for industries like banking, manufacturing, healthcare, and government administration bodies, where the demand for intelligent document processing software is high.

Challenges we ran into

As the problem statement does not specify any particular implementation, it's not possible to determine what challenges were encountered. However, in general, the following challenges may be encountered when developing a solution for automatically determining the quality of text documents:

• Defining the quality criteria: Determining the accuracy threshold for categorizing documents as GOOD, MODERATE, or POOR can be challenging and may require trial and error.
• Document variability: Text documents can come in various sizes, formats, and quality, making it challenging to develop a single solution that can handle all types of documents.
• Performance optimization: Ensuring that the solution processes each document within 1 second while maintaining accuracy can be a challenge.
• Integration with other technologies: Integrating the solution with other computer vision, image processing, and machine learning technologies may require significant effort and may result in compatibility issues.