Robust image retrieval using Hu invariants and principal components analysis

  • Authors:

  • C. Avilés-Cruz;A. Ferreyra-Ramirez;J. J. Ocampo-Hidalgo;I. Vazquez-Alvarez

  • Affiliations:

  • Departamento de Electrónica, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Azcapotzalco, Mexico D.F., Mexico;Departamento de Electrónica, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Azcapotzalco, Mexico D.F., Mexico;Departamento de Electrónica, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Azcapotzalco, Mexico D.F., Mexico;Departamento de Electrónica, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Azcapotzalco, Mexico D.F., Mexico

  • Venue:
  • ICCOMP'09 Proceedings of the WSEAES 13th international conference on Computers
  • Year:
  • 2009

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Abstract

A Robust image retrieval methodology is proposed in this paper; this methodology is based on Hu invariant moments (invariant to scale and translation) and principal components analysis (in order to eliminate any rotation). Image comparison is done by correlation. The proposed scheme was tested with hundred of structured images like: cars, trees, leaves, grass, glasses, tables, etc. Features characteristics are extracted from invariant moments, taken from window size estimation. From a query image, a set of features were estimated in order to compare to a set of images. Correlation function is applied to get image similarity, it is obtained a believe percentage value. As a methodology conclusion, we found that the invariant moments combined with principal component analysis gives excellent results in image retrieval task. An exhaustive study was performed with 1000 images.