Title :
Ancient degraded document image binarization based on texture features
Author :
Sehad, Abdenour ; Chibani, Youcef ; Cheriet, Mohamed ; Yaddaden, Yacine
Author_Institution :
ESI, Ecole Nat. Super. d´Inf., Algiers, Algeria
Abstract :
In this paper, we present a promising method for binarization of historical and degraded document images, based on texture features. The proposed method is an adaptive threshold-based. This latter is computed by using a descriptor based on a co-occurrence matrix. The proposed method is tested objectively, using DIBCO dataset degraded documents and subjectively, using a set of ancient degraded documents provided by a national library. The results are satisfactory and promising, and present an improvement to classical methods.
Keywords :
document image processing; feature extraction; history; image texture; matrix algebra; DIBCO dataset degraded documents; adaptive threshold-based method; ancient degraded document image binarization; cooccurrence matrix; historical document images; national library; texture features; Degradation; Equations; Image processing; Ink; Pattern recognition; Robustness; Signal processing; binarization; degraded document; texture; threshold;
Conference_Titel :
Image and Signal Processing and Analysis (ISPA), 2013 8th International Symposium on
Conference_Location :
Trieste
DOI :
10.1109/ISPA.2013.6703737