Image Retrieval Based on GA Integrated Color Vector Quantization and Curvelet Transform

  • Yungang Zhang
  • Tianwei Xu
  • Wei Gao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7331)


Color and shape information have been two important image descriptors in Content Based Image Retrieval (CBIR) systems. The focus of this research is to find a method representing images with color and shape information in the way of human visual perception. The image retrieval approach proposed here depends on the color and shape features extracted by color Vector Quantization (VQ) and the Digital Curvelet Transform (DCT), respectively. The extracted color and shape features were combined and weighted by Genetic Algorithm (GA), then used for image similarity measurement. Experimental results show that the GA combined features can bring about improved image retrieval performance.


Image retrieval color vector quantization curvelet transform genetic algorithm 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yungang Zhang
    • 1
    • 2
  • Tianwei Xu
    • 1
  • Wei Gao
    • 3
  1. 1.School of Information ScienceYunnan Normal UniversityKunmingChina
  2. 2.Department of Computer Science & Software EngineeringXi’anJiaoTong-Liverpool UniversitySuzhouChina
  3. 3.Department of MathematicsSoochow UniveristySuzhouChina

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