Research Article
Image Segmentation Based on Fuzzy Method
@INPROCEEDINGS{10.1007/978-3-031-30237-4_15, author={Yan Li and Decheng Yang and Baojin Zhang and Zhuo Zhai and Zhixu Luo}, title={Image Segmentation Based on Fuzzy Method}, proceedings={Machine Learning and Intelligent Communication. 7th EAI International Conference, MLICOM 2022, Virtual Event, October 23-24, 2022, Proceedings}, proceedings_a={MLICOM}, year={2023}, month={4}, keywords={Fuzzy Clustering Image Segmentation Super Pixel}, doi={10.1007/978-3-031-30237-4_15} }- Yan Li
Decheng Yang
Baojin Zhang
Zhuo Zhai
Zhixu Luo
Year: 2023
Image Segmentation Based on Fuzzy Method
MLICOM
Springer
DOI: 10.1007/978-3-031-30237-4_15
Abstract
Image is an important means for human to cognize the world, and image processing technology is also a key research direction in machine learning. In image processing technology, image segmentation is a very critical part of the current academic research hotspot. At present, the fuzzy C-means clustering (FCM) algorithm of image segmentation algorithm uses iterative method to classify samples, which needs less storage space and time. However, FCM algorithm also has many shortcomings, how to use clustering algorithm for real-time, automatic, high-quality image segmentation, has been a problem to be solved. In order to solve the massive data of color image, this paper uses the SLIC method to calculate the super-pixel image over-segmentation. Direct processing of the huge amount of information contained in a color image will degrade the performance of the algorithm. Therefore, image preprocessing is very important.
