Open AccessShip Target Image Segmentation Algorithm Based on Fuzzy Level Set
Author(s) -
Yu Zhang,
Yuntao Li,
Yao Guo,
Zheshuai Zhou
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1813/1/012054
Subject(s) - image segmentation , precondition , segmentation based object categorization , segmentation , artificial intelligence , scale space segmentation , fuzzy logic , computer science , pattern recognition (psychology) , computation , level set (data structures) , algorithm , computer vision , cluster analysis , image (mathematics) , fuzzy set , programming language
The effective recognition of ship target is very important for the protection of ocean rights, and the image segmentation is the precondition of the ship target recognition. To solve the two problems existing in the traditional level set graph, namely the increase of image segmentation and the increase of computation, the Fuzzy C-Means (FCM) and level set are introduced. A new algorithm for image segmentation based on fuzzy level set is proposed in this paper. The algorithm can use spatial fuzzy clustering to realize the parameter estimation and evolutionary adjustment. The algorithm is applied to optical remote sensing ship target image segmentation in complex sea environment, and the effectiveness of the proposed algorithm is verified by experiment results.