Sorting Speckled Granites (Nehbandan) and Measuring Their Surface Veining using Machine Vision
Hossein KardanMoghaddam1, Amir Rajaei2, MohamadReza Maraki3

1Hossein KardanMoghaddam*, Department of Computer Engineering, Birjand University of Technology, Birjand, Iran.
2Amir Rajaei, Faculty Member of Computer Engineering, Velayat University,Iranshahr, Iran.
3MohamadReza Maraki, Department of Materials Engineering, Birjand University of Technology, Birjand, Iran.

Manuscript received on 3 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 2574-2584 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4774098319/2019©BEIESP | DOI: 10.35940/ijrte.C4774.098319
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Abstract: Quality control and the appearance evaluation of stones are quite challenging in the industry today. The similar appearance of different stones containing the same minerals may result in economic losses, and if the customers fail to identify the type of slates delivered to them correctly, disagreements may arise between the buyers and granite vendors. This study is an attempt toward the automation of surface quality assessment of the Nehbandan(Iran) speckled granite and measurement of the surface patterns under fixed conditions using image processing techniques in order to classify the granite tiles based on their type and amount of impurities and veins. The experimental tests comparing the presented approach with the texture descriptors in the introduced dataset prove the efficiency of the proposed method and its applications under controlled conditions, including the classification of speckled granite tiles with different image resolutions.
Keywords: Image Processing, Speckled Granite, Segmentation of Minerals, Classification.

Scope of the Article: Classification