Issue 2
Apr.  2015
Turn off MathJax
Article Contents
MEI Langqi, GUO Jianming, LIU Qing. Research and Application of Texture Feature Extraction Based on Multi-features[J]. Journal of Transport Information and Safety, 2015, (2): 31-38. doi: 10.3963/j.issn1674-4861.2015.02.005
Citation: MEI Langqi, GUO Jianming, LIU Qing. Research and Application of Texture Feature Extraction Based on Multi-features[J]. Journal of Transport Information and Safety, 2015, (2): 31-38. doi: 10.3963/j.issn1674-4861.2015.02.005

Research and Application of Texture Feature Extraction Based on Multi-features

doi: 10.3963/j.issn1674-4861.2015.02.005
  • Publish Date: 2015-04-28
  • Texture is a significant visual feature which is commonly used to identify and distinguish the image .. This paper summarized and analyzed the current common method of texture feature extraction ,including Gray Level Co‐occurrence Matrix (GLCM ) ,Local Binary Pattern (LBP) and Discrete wavelet transform (DWT ) .With the weight of configuration parameters ,a new texture extraction method of multi‐features is proposed and implemented ,which com‐bines the three basic methods mentioned .The image texture description ability of different methods is compared through the tests on the image retrieval system .The results show that the average precision of texture feature extraction method based on multi‐feature combination increased 20% comparing to GLCM algorithm ;increased 9% comparing to LBP algo‐rithm ;increased 10% comparing to DWT algorithm ;and increased 15% comparing to Xu's texture feature extraction method when images were retrieved from Corel library .The new texture feature extraction method proposed in this paper combined the advantages of each method ,and had good rotation invariance and scale invariance .However ,it is necessary to extract the texture features of GLCM ,LBP and DWT at the same time ;the time required for the new texture feature extraction method is the sum of the three algorithms ,which limits its application in some practical cases .

     

  • loading
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (322) PDF downloads(0) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return