Degraded Historical Documents Images Binarization Using a Combination of Enhanced Techniques
This work addresses the challenge of document image binarization for historical archives, which is incremental as it builds on existing thresholding methods.
The paper tackled the problem of binarizing degraded historical document images by developing a multi-phase system that combines enhanced thresholding methods, including CLAHE for contrast improvement and noise removal techniques, resulting in improved precision and robustness as demonstrated on three benchmarks.
Document image binarization is the initial step and a crucial in many document analysis and recognition scheme. In fact, it is still a relevant research subject and a fundamental challenge due to its importance and influence. This paper provides an original multi-phases system that hybridizes various efficient image thresholding methods in order to get the best binarization output. First, to improve contrast in particularly defective images, the application of CLAHE algorithm is suggested and justified. We then use a cooperative technique to segment image into two separated classes. At the end, a special transformation is applied for the purpose of removing scattered noise and of correcting characters forms. Experimentations demonstrate the precision and the robustness of our framework applied on historical degraded documents images within three benchmarks compared to other noted methods.