Dictionary based color image retrieval

In this work the normalized dictionary distance (NDD) is presented and investigated. NDD is a similarity metric based on the dictionary of a sequence acquired from a data compressor. A dictionary gives significant information about the structure of the sequence it has been extracted from. We examine the performance of this new distance measure for color image retrieval tasks, by focusing on three parameters: the transformation of the 2D image to a 1D string, the color to character correspondence, and the image size. We demonstrate that NDD can outperform standard (dis)similarity measures based on color histograms or color distributions.