Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud Model
Uncertainty is an inherent part of image segmentation in real world applications. The use of new methods for handling incomplete information is of fundamental importance. Type-1 fuzzy sets used in conventional image segmentation cannot fully handle the uncertainties. Type-2 fuzzy sets and cloud mode...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Springer
2010-12-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://www.atlantis-press.com/article/2122.pdf |
| _version_ | 1818040902897106944 |
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| author | Tao Wu Kun Qin |
| author_facet | Tao Wu Kun Qin |
| author_sort | Tao Wu |
| collection | DOAJ |
| description | Uncertainty is an inherent part of image segmentation in real world applications. The use of new methods for handling incomplete information is of fundamental importance. Type-1 fuzzy sets used in conventional image segmentation cannot fully handle the uncertainties. Type-2 fuzzy sets and cloud model can handle such uncertainties in a better way because they provide us with more design degrees of freedom. The paper presents a comparison on the two approaches for image segmentation with uncertainty, that is, image thresholding based on type-2 fuzzy sets and cloud model. Firstly, the theoretical foundations of two methods are analyzed. Secondly, the processing of image segmentation with uncertainty is compared through two stages respectively, which is histogram analysis and optimum threshold selection. Finally, the experiments are divided in three groups, both synthetic and real images are used to investigate the performance of handling uncertainty in image segmentation, and some noisy images are also involved in to validate the performance of suppressing noise. The experimental results suggest that the conclusion of comparisons is effective. |
| first_indexed | 2024-12-10T08:21:55Z |
| format | Article |
| id | doaj.art-faf7b11329cc4b8f94cf27e09a801ad3 |
| institution | Directory Open Access Journal |
| issn | 1875-6883 |
| language | English |
| last_indexed | 2024-12-10T08:21:55Z |
| publishDate | 2010-12-01 |
| publisher | Springer |
| record_format | Article |
| series | International Journal of Computational Intelligence Systems |
| spelling | doaj.art-faf7b11329cc4b8f94cf27e09a801ad32022-12-22T01:56:20ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832010-12-013610.2991/ijcis.2010.3.s1.5Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud ModelTao WuKun QinUncertainty is an inherent part of image segmentation in real world applications. The use of new methods for handling incomplete information is of fundamental importance. Type-1 fuzzy sets used in conventional image segmentation cannot fully handle the uncertainties. Type-2 fuzzy sets and cloud model can handle such uncertainties in a better way because they provide us with more design degrees of freedom. The paper presents a comparison on the two approaches for image segmentation with uncertainty, that is, image thresholding based on type-2 fuzzy sets and cloud model. Firstly, the theoretical foundations of two methods are analyzed. Secondly, the processing of image segmentation with uncertainty is compared through two stages respectively, which is histogram analysis and optimum threshold selection. Finally, the experiments are divided in three groups, both synthetic and real images are used to investigate the performance of handling uncertainty in image segmentation, and some noisy images are also involved in to validate the performance of suppressing noise. The experimental results suggest that the conclusion of comparisons is effective.https://www.atlantis-press.com/article/2122.pdfType-2 fuzzy sets; cloud model; image thresholding; image segmentation; uncertainty. |
| spellingShingle | Tao Wu Kun Qin Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud Model International Journal of Computational Intelligence Systems Type-2 fuzzy sets; cloud model; image thresholding; image segmentation; uncertainty. |
| title | Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud Model |
| title_full | Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud Model |
| title_fullStr | Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud Model |
| title_full_unstemmed | Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud Model |
| title_short | Comparative Study of Image Thresholding Using Type-2 Fuzzy Sets and Cloud Model |
| title_sort | comparative study of image thresholding using type 2 fuzzy sets and cloud model |
| topic | Type-2 fuzzy sets; cloud model; image thresholding; image segmentation; uncertainty. |
| url | https://www.atlantis-press.com/article/2122.pdf |
| work_keys_str_mv | AT taowu comparativestudyofimagethresholdingusingtype2fuzzysetsandcloudmodel AT kunqin comparativestudyofimagethresholdingusingtype2fuzzysetsandcloudmodel |