Image thresholding using type II fuzzy sets

被引:216
作者
Tizhoosh, HR [1 ]
机构
[1] Univ Waterloo, Pattern Anal & Machine Intelligence Lab, Waterloo, ON N2L 3G1, Canada
关键词
image thresholding; fuzzy sets; type II fuzzy sets; measures of fuzziness; ultrafuzziness;
D O I
10.1016/j.patcog.2005.02.014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image thresholding is a necessary task in some image processing applications. However, due to disturbing factors, e.g. non-uniform illumination, or inherent image vagueness, the result of image thresholding is not always satisfactory. In recent years, various researchers have introduced new thresholding techniques based on fuzzy set theory to overcome this problem. Regarding images as fuzzy sets (or subsets), different fuzzy thresholding techniques have been developed to remove the grayness ambiguity/vagueness during the task of threshold selection. In this paper, a new thresholding technique is introduced which processes thresholds as type II fuzzy sets. A new measure of ultraftizziness is also introduced and experimental results using laser cladding images are provided. (c) 2005 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2363 / 2372
页数:10
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