An Improved Adaptive Level Set Method for Image Segmentation

Li Zhang*, Kai Teng Wu, Ping Li

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

8 引用 (Scopus)

摘要

In order to improve the accuracy of image segmentation, an improved adaptive level set method is proposed based on level set evolution without re-initialization method and adaptive distance preserving level set evolution method. A new definition of weight coefficient in evolution equations is the main innovation of this paper. The improved method can detect certain object boundaries, interior and exterior contours of an object, edges of multi-objects and weak boundaries of an object by synthetic and real images numerical experiments. Numerical results show that the improved adaptive level set method has faster segmentation speed and higher segmentation accuracy compared with the previous two methods, especially in weak boundaries and edges of multi-objects segmentation problems.

源语言英语
文章编号1854013
期刊International Journal of Pattern Recognition and Artificial Intelligence
32
5
DOI
出版状态已出版 - 1 5月 2018

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