Enhanced OCR for Noisy, Historical Documents ID: 2012-067

A novel method to significantly improve optical character recognition accuracy for degraded historical documents.

Technology Overview

This technology introduces an innovative approach to optical character recognition (OCR) by utilizing multiple thresholding binarization values to enhance the readability of noisy, historical documents. By combining the outputs from various thresholded images, the method aligns text outputs to create a lattice of word alternatives. This process involves calculating a lattice word error rate (LWER) to select the optimal text output, thereby improving the accuracy of OCR for documents that are typically challenging to process due to their degraded condition.

Key Advantages

• Significantly reduces word error rates in OCR outputs for historical documents
• Utilizes a novel approach by combining multiple thresholded images to enhance text readability
• Employs a lattice of word alternatives and calculates LWER for optimal accuracy
• Improves the utility of OCR in tasks requiring high precision in transcription and information extraction

Problems Addressed

• High error rates in OCR for degraded or noisy historical documents
• Difficulties in accurately extracting information or transcribing text from historical archives
• Limited effectiveness of traditional binarization techniques in processing degraded texts

Market Applications

• Archival digitization projects requiring accurate OCR of historical documents
• Libraries, museums, and academic institutions looking to enhance the accessibility of their collections
• Research initiatives in digital humanities and historical document preservation
• Technology platforms offering OCR services, particularly those dealing with archival materials

Additional Information

Technology ID: 2012-067
Sell Sheet: Download the Sell Sheet here
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Date Published: 30 June, 2025