Title :
Connectionist model binarization
Author :
Babaguchi, Noboru ; Yamada, Koji ; Kise, Koichi ; Tezuka, Yoshikazu
Author_Institution :
Dept. of Comm. Eng., Osaka Univ., Japan
Abstract :
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
Keywords :
learning systems; neural nets; pattern recognition; picture processing; back-propagation algorithm; connectionist model; image binarization; learning strategy; multilayer network; Data mining; Force measurement; Histograms; Inspection; Least squares methods; Mirrors; Pixel; Shape; Testing;
Conference_Titel :
Pattern Recognition, 1990. Proceedings., 10th International Conference on
Conference_Location :
Atlantic City, NJ
Print_ISBN :
0-8186-2062-5
DOI :
10.1109/ICPR.1990.119329
