Title :
An object attribute thresholding algorithm for document image binarization
Author :
Liu, Ying ; Feinrich, R. ; Srihari, Sargur N.
Author_Institution :
Center of Excellence for Document Analysis & Recognition, State Univ. of New York, Buffalo, NY, USA
Abstract :
Document image binarization is not a completely solved problem for unconstrained document images. Binarization algorithms, whether global or local, can easily fail on images with noisy or complex background, or poor contrast. The authors report preliminary results on a new approach to document image binarization, an algorithm based on gray scale histogram and run-length histogram analysis. Experimental results on unconstrained machine printed address blocks from the US letter mail stream show that over 99% of such address blocks can be correctly binarized
Keywords :
document image processing; image segmentation; optical character recognition; US letter mail stream; address blocks; complex background; document image binarization; gray scale histogram; machine printed address blocks; noisy background; object attribute thresholding algorithm; poor contrast; run-length histogram analysis; unconstrained document images; Algorithm design and analysis; Histograms; Image analysis; Image recognition; Image segmentation; Postal services; Shape; Statistics; Streaming media; Text analysis;
Conference_Titel :
Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
Conference_Location :
Tsukuba Science City
Print_ISBN :
0-8186-4960-7
DOI :
10.1109/ICDAR.1993.395732
