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An Improved Superpixel-based Fuzzy C-Means Method for Complex Picture Segmentation Tasks

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conference contribution
posted on 2023-08-30, 20:02 authored by Chen Keyi, Che Hangjun, Man-Fai Leung, Wang Yadi
Fuzzy c-means (FCM) has attracted wide attentions on picture segmentation as its fuzzy attribute matches the histogram distribution of a picture. However, the fuzzy c-means for the segmentation of a picture with massy noises is barely investigated. In this paper, an improved superpixel-based fuzzy c-means is proposed to segment a massy noise corrupted picture into more than two classes. Firstly, bilateral filtering is used to reduce the compact of noises and makes the picture smoother. Secondly an adaptive method is proposed to fuse the features of the original picture with filtered features. Thirdly simple linearly iterative clustering (SLIC) is used to detect the edge of the picture to avoid over-segmentation. Finally, the histogram-based fuzzy cmeans is used to get the segmentation result. In the experiments, the results show the proposed method achieves a 0.004 ∼ 0.014 higher mPA and 0.004 ∼ 0.06 higher mIoU than other seven algorithms. Besides the segmentation results also show that the over-segmentation is reduced.

History

Publisher

IEEE

Place of publication

Online

Name of event

14th International Conference on Advanced Computational Intelligence

Location

Wuhan, China

Event start date

2022-07-15

Event finish date

2022-07-17

File version

  • Accepted version

Language

  • eng

Legacy posted date

2022-06-15

Legacy creation date

2022-06-15

Legacy Faculty/School/Department

Faculty of Science & Engineering

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