An adaptive thresholding algorithm based on edge detection and morphological operations for document images
Renata F. P. Neves, Cleber Zanchettin, C.A.B. Mello · 2013
This paper presents a new algorithm to threshold document images. The proposed algorithm deal with complex background images, illumination and aspect variants, back-to-front interference, variation of brightness and different positioned shadows. The algorithm have two phases. The first one uses edge detection and morphological operations to identify the text on the image. The second phase uses the positions of the text to define the threshold value in an adaptive process. Our approach presents promising results in images with complex background released from the Document Image Binarization Contest (DIBCO) when compared with other literature and competition thresholding algorithms.