Artificial Bee Colony Optimizer for Historical Arabic Manuscript Images Binarization

Citation:
Fattah, M. A., A. E. H. , and A. F. A. Abdalla Mostafa, "Artificial Bee Colony Optimizer for Historical Arabic Manuscript Images Binarization", IEEE iInternational Computer Engineering Conference - ICENCO , Cairo, 30 Dec, 2015.

Date Presented:

30 Dec

Historical manuscript image binarization is a very
important step towards full word spotting system. In this paper,
we present a novel binarization algorithm based on artificial
bee colony optimizer. The proposed approach contains two
phases. The first phase is stretching the intensity level of the
image by contrast stretching filter and removing the noise
by image cleaning algorithm, the second phase is determining
the number of clusters, number of colony and iterations for
starting Artificial Bee Colony (ABC) algorithm.The proposed
approach is tested on a set of images collected from the electronic
Arabic manuscripts database and compared against three famous
binarization methods such as Niblack’s, Otsu’s and Savoul’s.
The Experimental results show that the proposed approach
is a promising approach and can obtain the desired results
better than the other compared methods