Adaptive Image Segmentation Method Based on Ncut
DOI:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In order to solve the problem that requires some factors by manual in the traditional Ncut algorithm, limit the generality of the algorithm, an adaptive image segmentation method is proposed by improving the traditional Ncut algorithm. First, instead of the two control parameters on the calculation of weight matrix that influence the segmentation results in the traditional Ncut algorithm by groups of potential theory; then in order to reduce the sensitive to the number of the cluster and the center of the cluster in the K-means algorithm, calculate on the eigenvector of the Ncut algorithm by the minimum spanning tree, to get the final number of cluster and the center, and then uses the K-means clustering algorithm to get the final segmentation result. The experimental results show that the proposed method not only improves the versatility of the algorithm, and the segmentation is good.

    Reference
    Related
    Cited by
Get Citation

黄仁,冯阿瑞.基于Ncut的自适应图像分割方法[J].土木与环境工程学报(中英文),2013,35(Z2):107~110

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: February 25,2014
  • Published:
Article QR Code