Effective and fast binarization method for combined degradation on ancient documents.

Area of Science:

• Computer Vision
• Image Processing
• Digital Humanities

Background:

• Document image binarization is crucial for digitizing historical texts.
• Combined degradations in ancient documents pose significant challenges for traditional binarization techniques.
• Existing methods often struggle with complex degradation patterns, impacting readability and analysis.

Purpose of the Study:

• To develop and evaluate a novel binarization method specifically designed for ancient documents with combined degradations.
• To improve the accuracy and efficiency of document image binarization for historical materials.
• To address limitations in current state-of-the-art binarization techniques for challenging document types.

Main Methods:

• A four-stage pipeline: histogram analysis for background uniformity, contrast enhancement, local adaptive thresholding for binarization, and artifact removal.
• Novel techniques are employed in histogram analysis, contrast enhancement, and local adaptive thresholding stages.
• The method was evaluated on diverse datasets, including private and public collections, with and without the contrast enhancement stage.

Main Results:

• The proposed method demonstrated superior performance in binarizing ancient documents compared to existing state-of-the-art approaches.
• Simulations indicated that the contrast enhancement stage significantly contributes to the method's effectiveness.
• The binarization process was found to be faster and more accurate, preserving finer details of the historical documents.

Conclusions:

• The novel binarization method offers a significant advancement for processing degraded ancient documents.
• The integrated approach effectively handles complex degradations, leading to cleaner and more accurate binarized outputs.
• This technique has the potential to enhance digital preservation and accessibility of historical document collections.