Mobile Image Mining for Granite Quality Detection

Abstract

Image Processing has a vital role in quality analysis of objects and presumably is one of the best ways of non destructive techniques. The project aims at detecting flaws if any in the granite blocks by analysis of their digital images. Two common defects, Crack and Mica contamination is studied by using hyper spectral image sensors. The unique characteristics of the defects are studied in hematite and geothite. To detect the mica contamination k-means segmentation algorithm is used. For crack detection, linear edge detection algorithm is applied and further processing is done to discriminate edges of cracks. Thus the algorithm categorizes the granite as defect less or defected granite.

Authors and Affiliations

S. B. Nithiya, M. Vivek Yoganand, M. Girija,

Keywords

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  • EP ID EP19152
  • DOI -
  • Views 275
  • Downloads 7

How To Cite

S. B. Nithiya, M. Vivek Yoganand, M. Girija, (2014). Mobile Image Mining for Granite Quality Detection. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(12), -. https://europub.co.uk/articles/-A-19152