Feature Extraction of Images Texture Based on Co-occurrence Matrix

  • Hadia S. Abd allah Department of Computer Science, College of Computer Sciences &Mathematics, University of Mosul, Iraq.
  • Wijdan Yassen Department of Computer Science, College of Education for pure Science, University of Basrah, Iraq.
  • khalil I. Alsaif
Keywords: GLCM, Feature Extracted ,Texture


There are many techniques to extracted object properties in an image. In this research a co-occurrence  matrix has been to adopted for feature extraction of English letters. English letters of size 14 and font time new roman have been stored as image, then preproced by apply truncation to take off all blank area, then filtered to make it noise free. Energy, contrast, correlation and homogeneity of the co-occurrence  matrix properties for the stored character images were calculated. Another character models with different size and fonts were adopted to make the database able to cover a wide range of character images for character recognition and classification . Applied technique shows that a companation features can be extracted as new properties for letters images and give good results. The experimental results of the proposed algorithm have proved that both energy and homogeneity features have given high recognition  compared with the remaining other properties.


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How to Cite
Abd allah, H., Yassen, W. and Alsaif, khalil (2019) “Feature Extraction of Images Texture Based on Co-occurrence Matrix”, Zanco Journal of Pure and Applied Sciences, 31(2), pp. 60-69. doi: 10.21271/zjpas.31.s2.8.