Implementasi Kombinasi Feature Extraction untuk Content Based Image Retrieval

Authors

  • Fredy Windana STT STIKMA Internasional
  • Moechammad Sarosa Politeknik Negeri Malang
  • Purnomo Budi Santoso Jurusan Teknik Industri Fakultas Teknik Universitas Brawijaya

DOI:

https://doi.org/10.21776/jeeccis.v8i2.257

Abstract

In this research, the CBIR method used several combination of feature extraction methods, such as a combination between LCH (HSV) and DC Coefficient, a combination between 2 nd Order Statistic GLCM Sub Block and DC Coefficient, and a combination between LCH (HSV), 2 nd Order Statistic GLCM Sub Block and DC Coefficient. Sample image experiment test was used from CorelDB dataset. The result from the research showed performance component value of Non Interpolating Average Precision method performed by the combination of LCH (HSV) and DC Coefficient performance rate was about 23%. While the variance of the combination of 2 nd order statistic GLCM sub block and coefficient DC and the combination of LCH (HSV), 2 nd order statistic GLCM sub block and coefficient DC showed performance rate was about 12%.Keywords – CBIR, LCH, GLCM, DC Coefficient

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Published

2014-12-01

How to Cite

[1]
F. Windana, M. Sarosa, and P. B. Santoso, “Implementasi Kombinasi Feature Extraction untuk Content Based Image Retrieval”, jeeccis, vol. 8, no. 2, pp. pp.169–174, Dec. 2014.

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Articles