IEEE Trans Image Process - IPSILON: incremental parsing for semantic indexing of latent concepts.

Tópicos

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Resumo

A new framework for content-based image retrieval, which takes advantage of the source characterization property of a universal source coding scheme, is investigated. Based upon a new class of multidimensional incremental parsing algorithm, extended from the Lempel-Ziv incremental parsing code, the proposed method captures the occurrence pattern of visual elements from a given image. A linguistic processing technique, namely the latent semantic analysis (LSA) method, is then employed to identify associative ensembles of visual elements, which lay the foundation for intelligent visual information analysis. In 2-D applications, incremental parsing decomposes an image into elementary patches that are different from the conventional fixed square-block type patches. When used in compressive representations, it is amenable in schemes that do not rely on average distortion criteria, a methodology that is a departure from the conventional vector quantization. We call this methodology a parsed representation. In this article, we present our implementations of an image retrieval system, called IPSILON, with parsed representations induced by different perceptual distortion thresholds. We evaluate the effectiveness of the use of the parsed representations by comparing their performance with that of four image retrieval systems, one using the conventional vector quantization for visual information analysis under the same LSA paradigm, another using a method called SIMPLIcity which is based upon an image segmentation and integrated region matching, and the other two based upon query-by-semantic-example and query-by-visual-example. The first two of them were tested with 20,000 images of natural scenes, and the others were tested with a portion of the images. The experimental results show that the proposed parsed representation efficiently captures the salient features in visual images and the IPSILON systems outperform other systems in terms of retrieval precision and distortion robustness.

Resumo Limpo

new framework contentbas imag retriev take advantag sourc character properti univers sourc code scheme investig base upon new class multidimension increment pars algorithm extend lempelziv increment pars code propos method captur occurr pattern visual element given imag linguist process techniqu name latent semant analysi lsa method employ identifi associ ensembl visual element lay foundat intellig visual inform analysi d applic increment pars decompos imag elementari patch differ convent fix squareblock type patch use compress represent amen scheme reli averag distort criteria methodolog departur convent vector quantiz call methodolog pars represent articl present implement imag retriev system call ipsilon pars represent induc differ perceptu distort threshold evalu effect use pars represent compar perform four imag retriev system one use convent vector quantiz visual inform analysi lsa paradigm anoth use method call simplic base upon imag segment integr region match two base upon querybysemanticexampl querybyvisualexampl first two test imag natur scene other test portion imag experiment result show propos pars represent effici captur salient featur visual imag ipsilon system outperform system term retriev precis distort robust

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