An improved image segmentation algorithm based on rough set

The main information of image focus in the target area, and the rest part contains a large amount of redundancy. The image segmentation is an important technology in image processing. This paper presents an improved rough set image segmentation algorithm, which is based on the theory of fuzzy C-mean...

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Bibliographic Details
Published in2016 IEEE International Conference on Computational Electromagnetics (ICCEM) pp. 144 - 148
Main Authors Fan Liao, Ruichang Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.02.2016
Subjects
Classification algorithms
Clustering algorithms
Data mining
Feature extraction
Image segmentation
Rough sets
Visualization
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Summary:The main information of image focus in the target area, and the rest part contains a large amount of redundancy. The image segmentation is an important technology in image processing. This paper presents an improved rough set image segmentation algorithm, which is based on the theory of fuzzy C-means clustering, the human visual attention model and relative position. Combination of fuzzy clustering results, visual saliency map and relative position map, it constitutes the knowledge representation system, and then obtains the related decision rules through the attribute reduction. The experiment shows that this algorithm has good segmentation effect compared with traditional methods.
DOI:10.1109/COMPEM.2016.7588638