Image analysis – Image segmentation – Distinguishing text from other regions
Patent
1998-03-25
2000-12-12
Chang, Jon
Image analysis
Image segmentation
Distinguishing text from other regions
382205, 382224, 358462, G06K 956, G06K 962
Patent
active
061609137
ABSTRACT:
An image processing method for detection and removal of halftone dots includes converting a gray scale image into a binary thresholded image with halftone dots; identifying halftone regions within the binary thresholded image; and removing halftone dots from the identified halftone regions. The identifying halftone regions step is effected by classifying the binary thresholded image to produce a halftone classification map; reclassifying the halftone classification map to produce a halftone reclassification map of lines with plural halftone pixels in each line; merging the halftone pixels in each line in the halftone reclassification map to produce a halftone line map; and merging the lines of the halftone line map to produce a halftone region map.
REFERENCES:
patent: 4194221 (1980-03-01), Stoffel
patent: 4403257 (1983-09-01), Hsieh
patent: 4707745 (1987-11-01), Sakano
patent: 4722008 (1988-01-01), Ibaraki et al.
patent: 5131049 (1992-07-01), Bloomberg et al.
patent: 5291309 (1994-03-01), Semasa
patent: 5381241 (1995-01-01), Kawanaka et al.
patent: 5392365 (1995-02-01), Steinkirchner
patent: 5583659 (1996-12-01), Lee et al.
patent: 5617216 (1997-04-01), Wada
patent: 5987221 (1999-11-01), Bearss et al.
Basile Joseph M.
Beato Louis J.
Lee Yongchun
Mielcarek Stanley A.
Chang Jon
Eastman Kodak Company
Sales Milton S.
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