Usetech Case: HANDWRITING RECOGNITION

Today, we want to tell you about one of our machine vision based cases.

Linguists studying ancient texts have been using computer text processing for a long time. However, such digital solutions ensure proper recognition accuracy only for common languages. Arabic studies still have no AI-based developments for text analysis. Difficult scripts recognition and missing areas restoration are the main challenges in paleographic works.

PROBLEMATICS:

Time and Resource Costs

Manual recognition takes much time, especially if the volume of data is large. This can significantly slow down work flows and increase Arabic data processing costs.

Difficulty of Results Interpretation

The complexity of handwriting and the lack of standardization make the process extremely labor-intensive, and information might also be distorted as a result of manual translation. Arabic handwriting is highly diverse and complex; moreover, there is no unified writing system, which complicates the correct interpretation task.

Human Errors

Manual processing of large data volumes requires significant effort and concentration, which can lead to fatigue and poor performance. Human errors can lead to inaccuracies and mistakes in recognition, especially when working with illegible or non-standard handwriting.

Handwriting Recognition Benefits of Our Solution

• Fast processing of large data volumes without sacrificing quality
• Decrease in analysis and interpretation time
• Routine tasks automation
• Cultural heritage preservation, ancient writing studies
• Availability of information due to its digitalization
• Decrease in errors resulting from typos and incorrect character recognition

Ready to learn more about this solution? Contact us by contact@usetech.com