  Document image binarization is the initial step and a crucial in many
document analysis and recognition scheme. In fact, it is still a relevant
research subject and a fundamental challenge due to its importance and
influence. This paper provides an original multi-phases system that hybridizes
various efficient image thresholding methods in order to get the best
binarization output. First, to improve contrast in particularly defective
images, the application of CLAHE algorithm is suggested and justified. We then
use a cooperative technique to segment image into two separated classes. At the
end, a special transformation is applied for the purpose of removing scattered
noise and of correcting characters forms. Experimentations demonstrate the
precision and the robustness of our framework applied on historical degraded
documents images within three benchmarks compared to other noted methods.
