CVPIC image retrieval based on block colour co-occurance matrix and pattern histogram (MA-P5)

Author(s) : Gerald Schaefer (Nottingham Trent University, UK) Simon Lieutaud (Nottingham Trent University, UK) Guoping Qiu (University of Nottingham, UK)

Abstract : Compressed domain image retrieval is going to play an increasingly important role in the future. It allows the calculation of image features and hence content-based image retrieval (CBIR) to be performed directly on the compressed data without the need of decoding it beforehand. The Colour Visual Pattern Image Coding (CVPIC) technique represents a compression algorithm where the compressed form is directly meaningful. In this paper we introduce a compressed domain retrieval algorithm based on CVPIC that makes immediate use of the fact that colour and pattern information is readily available in the CVPIC domain. Colour features are exploited by building a block co-occurance matrix of colour indices while shape information is represented through pattern histograms. Combining these two types of descriptors results in an efficient and effective image retrieval method that even outperforms popular pixel-based algorithms such as colour histograms, colour coherence vectors and colour correlograms.

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