Fuzzy inference and logical level methods for binary graphic/character image extraction

Thresholding is one of the most important approaches to image segmentation. It has been widely used to characterize many images containing some objects of reasonably uniform brightness against a background of differing brightness. Typical examples include handwritten/typewritten text and microscope...

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Bibliographic Details
Main Authors: Kang, Byoung-Ho, Han, Gyu-Seo, Kim, Hong-Gee, Kim, Jin-Seo, Yoon, Chang-Rak, Cho, Maeng-Sub
Format: Conference Proceeding
Language:English
Subjects:
Brightness
Digital images
Engineering drawings
Fuzzy logic
Graphics
Image processing
Image segmentation
Optical character recognition software
Optical noise
Pixel
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Summary:Thresholding is one of the most important approaches to image segmentation. It has been widely used to characterize many images containing some objects of reasonably uniform brightness against a background of differing brightness. Typical examples include handwritten/typewritten text and microscope bio-medical samples. Even though it can be applied to the image processing widely, there is no robust thresholding technique to circumvent noisy image. In this study, firstly, the published character/graphic image extraction techniques were reviewed and investigated and new thresholding technique such as fuzzy inference and modified logical level are proposed. In fuzzy inference technique, new methods of fuzzification, fuzzy rule, and defuzzification are introduced for lower error and high speed image binarization.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.1998.727581