Open AccessVariation Method Overview of Image Segmentation
Author(s) -
Yuanyuan Tian,
Yibing Xue
Publication year - 2020
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 - 10.1088/1742-6596/1487/1/012012
Subject(s) - segmentation , image segmentation , variation (astronomy) , computer science , artificial intelligence , scale space segmentation , segmentation based object categorization , computer vision , image (mathematics) , process (computing) , region growing , field (mathematics) , pattern recognition (psychology) , mathematics , physics , astrophysics , pure mathematics , operating system
With the research and development of image segmentation methods for several decades, the various theories and methods have been applied to the image segmentation. Among the many methods of image segmentation, the variation method is applied widely, because its model process is easier, the expansibility of the method is better and the implementation process is simple. On the basics of many achievements of variation method research of image segmentation recently, the variation method of image segmentation is divided into the model based on the boundary and the field according to various structural driving force based on energy functional. In this paper, we analyze these models based on these two methods and discuss their advantages and disadvantages. Relevant innovation algorithms and breakthrough progresses recently have been researched. Some development directions of image segmentation variation method have been given. The application field and development of variation image segmentation still have great research value.