Artificial bee colony optimizer for historical Arabic manuscript images binarization

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.