TEXTURE MATERIAL CLASSIFICATION BASED ON GLCM AND TAMURA FUSION
DOI:
Author:
Affiliation:

1.Nanjing University of Information Science & Technology;2.Nanjing University Of Information Science &3.Technology

Clc Number:

Fund Project:

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

    Virtual reality haptic rendering has higher requirements for image texture feature extraction. Texture factors are complex and irregular. A single texture extraction algorithm can not accurately describe the characteristics of image texture. Therefore, a texture material classification algorithm based on GLCM and Tamura fusion features is proposed. In addition, this paper optimizes the GLCM and proposes T-GLCM operator, which improves the rotation invariance of GLCM pair and reduces a lot of redundant information. In this paper, the Tamura texture features are used to quantify the image, and then the feature regions are quantized and cascaded into a set of feature vectors. The texture features of T-GLCM are fused, and the texture materials are classified by support vector machine (SVM). The experimental results show that the algorithm has higher classification accuracy and is better than the traditional texture feature extraction algorithm.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:July 02,2021
  • Revised:October 15,2021
  • Adopted:November 23,2021
  • Online:
  • Published:

Address:No. 219, Ningliu Road, Nanjing, Jiangsu Province

Postcode:210044

Phone:025-58731025