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Article . 2022
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A New Hybrid Image Thresholding Technique Based On Local and Global Parameters Applied to Ancient Document Analysis

Authors: Saïd ECH-CHADI; Hajar ELKIHEL; Youness ECHCHADI;

A New Hybrid Image Thresholding Technique Based On Local and Global Parameters Applied to Ancient Document Analysis

Abstract

Digital archiving has helped in the development of the exploitation of historical documents, but the number of old documents analysed in national archives and libraries that are specialized in old documents remains very little and dependent on advances in the field of image processing especially thresholding [1]. In this paper we propose a method for segmenting text in ancient documents based on a new hybrid adaptive binarization technique which integrates local and global parameters, in consideration of resolving unsolved problem in thresholding of degraded document images [2] due to the low quality of this type of image, the main idea of our method is to combine the local behaviour and the global behaviour of lighting and contrast variation within the image. The direct application of our approach will improve the quality of processing of old documents, thus character recognition and in-depth analyzes based on contrasts and the types of inks used, will make it possible to better understand the cultural and historical riches existing in old documents.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green