Abstract
An image index model has been proposed that will help in the retrieval of images based on query by example. It is based on Vector Quantization (VQ). VQ represents the similarity of the images based on the codebook that is used for compression. An index is constructed based on the encoding distortion (ED) values using the Terrier Direct Index. It is found that some image transformations do not have any impact on the ED values and the retrieval accuracy is higher, efficient and faster. It can be combined with the cube index model for text documents to give a single structure for facilitating both image and text retrieval.
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Janet, B., Reddy, A.V., Domnic, S. (2010). An Image Index Model for Retrieval. In: Das, V.V., et al. Information Processing and Management. BAIP 2010. Communications in Computer and Information Science, vol 70. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12214-9_80
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DOI: https://doi.org/10.1007/978-3-642-12214-9_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12213-2
Online ISBN: 978-3-642-12214-9
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