Image Thresholding Based on Index of Fuzziness and Fuzzy Similarity Measure

被引：0

作者：

Pratamasunu, Gulpi Qorik Oktagalu ^{[1
]}

Arifin, Agus Zainal ^{[2
]}

Yuniarti, Anny ^{[2
]}

Navastara, Dini Adni ^{[2
]}

Wijaya, Arya Yudhi ^{[2
]}

Khotimah, Wijayanti Nurul ^{[2
]}

Hu, Zhencheng ^{[3
]}

Asano, Akira ^{[4
]}

机构：

[1] Sekolah Tinggi Teknol Nurul Jadid, Dept Informat, Probolinggo, Indonesia

[2] Inst Teknol Sepuluh Nopember, Fac Informat Technol, Dept Informat, Surabaya, Indonesia

[3] Kumamoto Univ, Grad Sch Sci & Technol, Kumamoto 860, Japan

[4] Kansai Univ, Dept Informat, Fac Informat, Suita, Osaka, Japan

来源：

2015 IEEE 8TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (IWCIA) PROCEEDINGS | 2015年

关键词：

image thresholding; index of fuzziness; fuzzy similarity measure; SEGMENTATION; SETS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose an automatic image thresholding method based on an index of fuzziness and a fuzzy similarity measure. This work aims at overcoming the limitation of the existing method which is semi-supervised. Using an index of fuzziness, two initial regions of gray levels located at the boundaries of the histogram are defined based on the fuzzy region. Then the threshold point is found by using a fuzzy similarity measure. No prior knowledge of the image is required. Experiments on practical images illustrate the effectiveness of the proposed method.

引用

页码：161 / 166

页数：6

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