A Comparative Study of Filtering Approaches Applied to Color Archival Document Images

lib:fab4531ade19e490 (v1.0.0)

Authors: Walid Elhedda,Maroua Mehri,Mohamed Ali Mahjoub
ArXiv: 1908.09007
Document:  PDF  DOI 
Abstract URL: https://arxiv.org/abs/1908.09007v1


Current systems used by the Tunisian national archives for the automatic transcription of archival documents are hindered by many issues related to the performance of the optical character recognition (OCR) tools. Indeed, using a classical OCR system to transcribe and index ancient Arabic documents is not a straightforward task due to the idiosyncrasies of this category of documents, such as noise and degradation. Thus, applying an enhancement method or a denoising technique remains an essential prerequisite step to ease the archival document image analysis task. The state-of-the-art methods addressing the use of degraded document image enhancement and denoising are mainly based on applying filters. The most common filtering techniques applied to color images in the literature may be categorized into four approaches: scalar, marginal, vector and hybrid. To provide a set of comprehensive guidelines on the strengths and weaknesses of these filtering approaches, a thorough comparative study is proposed in this article. Numerical experiments are carried out in this study on color archival document images to show and quantify the performance of each assessed filtering approach.

Relevant initiatives  

Related knowledge about this paper Reproduced results (crowd-benchmarking and competitions) Artifact and reproducibility checklists Crowd-benchmarking tools Reproducibility initiatives

Comments  

Please log in to add your comments!
If you notice any inapropriate content that should not be here, please report us as soon as possible and we will try to remove it within 48 hours!