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Enhancing the retrieval performance in content based image retrieval using meta-heuristic approach

Author

Listed:
  • S. Umamaheswaran
  • N. Suresh Kumar
  • K. Ganesh
  • P. Sivakumar

Abstract

Multimedia and digital image database management have undergone major transformation significantly in recent years in domains like data mining, medical imaging, weather forecasting and remote sensing, etc. CBIR is an important tool, useful to retrieve the required image precisely and effectively from large databases. This paper proposes the use of low level visual content features viz, mean value and colour histogram, to retrieve the colour feature and gray level co-occurrence matrix is proposed for retrieval of the texture feature. IGA is integrated with the above said low level features to derive refined results for query image matching from the database and to differentiate retrieval performance among the image features. The proposed method yields an accurate and faster retrieval from a Corel image database.

Suggested Citation

  • S. Umamaheswaran & N. Suresh Kumar & K. Ganesh & P. Sivakumar, 2017. "Enhancing the retrieval performance in content based image retrieval using meta-heuristic approach," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 26(2), pages 220-235.
  • Handle: RePEc:ids:ijbisy:v:26:y:2017:i:2:p:220-235
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