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Multimedia Tools and Applications

, Volume 74, Issue 4, pp 1469–1488 | Cite as

K-means based histogram using multiresolution feature vectors for color texture database retrieval

  • Cong BaiEmail author
  • Jinglin Zhang
  • Zhi Liu
  • Wan-Lei Zhao
Article

Abstract

Colorand texture are two important features in content-based image retrieval. It has been shown that using the combination of both could provide better performance. In this paper, a K-means based histogram (KBH) using the combination of color and texture features for image retrieval is proposed. Multiresolution feature vectors representing color and texture features are directly generated from the coefficients of Discrete Wavelet Transform (DWT), and K-means is exploited to partition the vector space with the objective to reduce the number of histogram bins. Thereafter, a fusion of z-score normalized Chi-Square distance between KBHs is employed as the similarity measure. Experiments have been conducted on four natural color texture data sets to examine the sensitivity of KBH to its parameters. The performance of the proposed approach has been compared with state-of-the-art approaches. Results evaluated in terms of Precision-Recall and Average Retrieval Rate (ARR) show that our approach outperforms the referred approaches

Keywords

Color texture retrieval K-means Discrete wavelet transform (DWT) Z-score normalization 

Notes

Acknowledgments

This work was supported by National Natural Science Foundation of China under Grant No. 61171144, the Key (Key grant) Project of Chinese Ministry of Education (No. 212053), and the Innovation Program of Shanghai Municipal Education Commission (No. 12ZZ086)

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Cong Bai
    • 1
    Email author
  • Jinglin Zhang
    • 2
  • Zhi Liu
    • 3
    • 4
  • Wan-Lei Zhao
    • 5
  1. 1.College of Computer ScienceZhejiang University of TechnologyHangzhouChina
  2. 2.IETR UMR CNRS 6164INSA de Rennes, Université Européenne de BretagneRennesFrance
  3. 3.School of Communication and Information EngineeringShanghai UniversityShanghaiChina
  4. 4.IRISA/INRIA-RennesRennesFrance
  5. 5.INRIA-RennesRennesFrance

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