Connectionist model binarization
The application of a connectionist model to an image binarization method called connectionist model binarization (CMB) is discussed. CMB employs a multilayer network of a connectionist model whose input and output are a histogram and a desirable threshold for binarization, respectively. This network is trained with a back-propagation algorithm to output a threshold which gives a visually suitable binarised image against any histogram. The details of CMB are described, and its learning strategy and binarization performance are discussed.<<ETX>>