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A fractals-inspired approach to binary image database indexing and retrieval

Une approche inspirée du codage fractal pour l’indexation et la récupération d’images binaires

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Abstract

This paper applies ideas from fractal compression and optimization theory to attack the problem of efficient content-based image indexing and retrieval. Similarity of images is measured by block matching after optimal (geometric, photometric, etc.) transformation. Such block matching which, by definition, consists of localized optimization, is further governed by a global dynamic programming technique (Viterbi algorithm) that ensures continuity and coherence of the localized block matching results. Thus, the overall optimal transformation relating two images is determined by a combination of local block-transformation operations subject to a regularization constraint. Experimental results on some limited subsets of still binary images from the mpeg-7 database demonstrate the power and potential of the proposed approach.

Résumé

Cet article reprend certaines idées du codage fractal et de la théorie de l’optimisation pour tenter de résoudre le difficile problème de l’indexation et de la récupération d’images à partir du contenu. La similarité entre images est mesurée par appariements de blocs incluant des transformations photométriques et géométriques. Une technique d’appartement de blocs qui consiste, par définition, à optimiser localement, est ensuite gérée globalement par une technique de programmation dynamique (algorithmes de Viterbi) qui garantit la continuité et la cohérence des résultats locaux d’appariement de blocs. Ainsi, la transformation optimale globale reliant deux images est déterminée par une combinaison d’opérations locales sur des blocs d’image soumise à une contrainte de régulation. Des simulations menées sur un sousensemble limité d’images binaires extraites de la base d’images mpeg-7 démontrent la puissance et le potentiel de l’approche proposée dans cet article.

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Authors and Affiliations

  1. Dept. of Multimedia Communication, Institut Eurecom, BP 193, F-06904, Sophia Antipolis, France

    Mathieu Vissac & Jean-Luc Dugelay

  2. Dept. of Electrical and Computer Engineering, SCL, University of California, Santa Barbara, California

    Kenneth Rose

Authors
  1. Mathieu Vissac
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  2. Jean-Luc Dugelay
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  3. Kenneth Rose
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Correspondence to Jean-Luc Dugelay or Kenneth Rose.

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Vissac, M., Dugelay, JL. & Rose, K. A fractals-inspired approach to binary image database indexing and retrieval. Ann. Télécommun. 55, 194–200 (2000). https://doi.org/10.1007/BF03001912

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  • DOI: https://doi.org/10.1007/BF03001912

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