Fast Retrieval from Image Databases via Binary Haar Wavelet Transform on the Color and Edge Directivity Descriptor

نویسندگان

  • Savvas A. Chatzichristofis
  • Yiannis S. Boutalis
  • Avi Arampatzis
چکیده

In this paper, we are evaluating several accelerating techniques for content-based image retrieval, suitable for the Color and Edge Directivity Descriptor (CEDD). To date, the experimental results presented in the literature have shown that the CEDD achieves high rates of successful retrieval in benchmark image databases. Although its storage requirements are minimal, only 54 bytes per image, the time required for retrieval may be practically too long when searching on large databases. The proposed technique utilizes the Binary Haar Wavelet Transform in order to extract from the CEDD a smaller and more efficient descriptor, with a size of less than 2 bytes per image, speeding up retrieval from large image databases. This descriptor describes the CEDD, but not necessarily the image from which it is extracted. The effectiveness of the proposed method is demonstrated through experiments performed on several known benchmarking databases. Keywords-CEDD; Binary Haar Wavelet Transform; ContentBased Image Retrieval;

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تاریخ انتشار 2011