@inproceedings{9b0e317812c040488a616f724aad0cf4,
title = "Adaptive fuzzy clustering algorithm with local information and markov random field for image segmentation",
abstract = "Fuzzy c-means (FCM) clustering as one of the clustering method is widely used in image segmentation field, but some methods based on FCM are unable to obtain satisfactory performance for image segmentation under intense noise condition. This paper presents a novel local spatial information based fuzzy c-means clustering and Markov random field method for image segmentation. In the method, a new dissimilarity function is proposed by using the prior relationship degree and local neighbor distances, which enhances its resistance to noise. And a novel prior probability approximation is considered with spatial Euclidean distance and the difference of the mean color level between the center pixel and its neighborhoods. Experiments over synthetic images, real-world images and brain MR images indicate that the proposed method obtains better segmentation performance, compared to the FCM extended methods.",
keywords = "Fuzzy c-means clustering, Image segmentation, Local information, Markov random field",
author = "Jialiang Hu and Ying Wen",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2018.; 25th International Conference on Neural Information Processing, ICONIP 2018 ; Conference date: 13-12-2018 Through 16-12-2018",
year = "2018",
doi = "10.1007/978-3-030-04212-7\_15",
language = "英语",
isbn = "9783030042110",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "170--180",
editor = "Seiichi Ozawa and Leung, \{Andrew Chi Sing\} and Long Cheng",
booktitle = "Neural Information Processing - 25th International Conference, ICONIP 2018, Proceedings",
address = "德国",
}