A Novel Approach for Texture Feature Extraction to Retrieve Texture Images using Gray-Level Co-occurrence Matrix (GLCM)

Authors

  • Vinodha H. N. Computer Science and Engineering Department, U.B.D.T College of Engineering, Visvesvaraya Technological University, Davangere, Karnataka, India
  • Mohamed Rafi Computer Science and Engineering Department, U.B.D.T College of Engineering, Visvesvaraya Technological University, Davangere, Karnataka, India

DOI:

https://doi.org/10.37591/joipprp.v1i3.201

Keywords:

Content based image retrieval (CBIR), texture-GLCM, processing time, execution time, recall, precision

Abstract

Image retrieval plays an important role in many of the areas. Content based image retrieval (CBIR) is used for browsing most similar images from the large database. Texture is an important characteristics used in identifying the region of interest or objects in an image. In this image retrieval method, texture method is used to extract the features and retrieves the similar images based on similarity of the features. In the texture method, gray-level co-occurrence matrix (GLCM) texture method is used to extract the texture features. After extracting, the features are compared with the database images and distance is calculated using the Euclidian distance. Finally, similar images are retrieved according to the user satisfaction. Performance of the system is calculated using the processing time, execution time, precision and recall rate metrics.

References

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Sandhu A., Kochhar A. Presented the paper: Content based image retrieval using texture, color and shape for image analysis. Int J Comp. 2012; 3(1) 149–152p.

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Published

2014-12-28

Issue

Vol. 1 No. 3 (2014)

Section

Research Articles

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