A local thresholding algorithm for images of handwritten historical documents

This paper presents a new algorithm to threshold images of historical documents. The thresholding phase is one of the most important phase in document recognition. An error on it could turn impossible the recognition of the document content. The proposed algorithm is divided into three phases. The first is responsible to indentify the main objects of the image. The second phase divides the image into sub-images according to the previous identification. And the latest phase evaluates a local threshold for each sub-image and proceeds with the binarization of each region. Our approach presented good results in images with complex background and it obtained the best performace when compared with other thresholding algorithms based on the measures used in DIBCO 2009.