• Abdul-Adheem Zaily Hameed Anbar University – College of Computer Science – Department of Computer Science – Anbar – Iraq
  • Muzhir Shaban Al-Ani Department of Computer Science, College of Science and Technology, University of Human Development, Sulaimani, KRG, Iraq
  • Faik Hammad Anter Anbar University – College of Sciences – Department of physics – Anbar – Iraq



Surface Analysis, Composite Materials, Image Analysis, reinforcing particle materials, Nano Alumina (NanoAl2O3) Analysis and Nano Titanium (NanoTiO2) Analysis


Composite material is a material constructed of two or more materials that leads with different physical or chemical characteristics. Nano Alumina (NANO AL2O3) and Nano Titanium (NANO TIO2) are normally used to construct the composite material. The fundamental of texture analysis seeks to derive a general efficient and compact quantitative description of textures so that various mathematical operations can be used to achieve, compare and transform of texture characteristics. Many mechanical and physical methods are used to measure the surface characteristics. Some of these methods suffered from accurate description of material surface. In addition, the details of material surface are not clear via applying the traditional methods for surface analyzing. This work is concentrated on combining many functions and steps of image processing method to understand and analyze the surface characteristics of the composite material (Nano Alumina and Nano Titanium). The implemented approach including many steps: image enhancement, texture analysis, edge detection and contour analysis. This approach leads to explain, extract, analyze and evaluate the characteristics of surface texture of the composite material via measuring of mean values for original gray image, adjusted gray image, equalized gray image and adapted gray image. The average mean values of Nano Alumina are 103, 110, 128 and 134 for the applied method respectively. The average mean values of Nano titanium are 120, 123, 125 and 129 respectively. As a conclusion the implemented approach of surface texture analysis indicated that there is a significant improvement at the surface characteristics for both equalization and adaptive methods compared with the adjustment method.


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