Image characterization and classification ...
Document type :
Compte-rendu et recension critique d'ouvrage
DOI :
Title :
Image characterization and classification by physical complexity
Author(s) :
Zenil, Hector [Auteur]
Systèmes Multi-Agents et Comportements [SMAC]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Gaucherel, Cédric [Auteur]
Botanique et Modélisation de l'Architecture des Plantes et des Végétations [UMR AMAP]
Delahaye, Jean-Paul [Auteur]
Systèmes Multi-Agents et Comportements [SMAC]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Systèmes Multi-Agents et Comportements [SMAC]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Gaucherel, Cédric [Auteur]
Botanique et Modélisation de l'Architecture des Plantes et des Végétations [UMR AMAP]
Delahaye, Jean-Paul [Auteur]

Systèmes Multi-Agents et Comportements [SMAC]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Journal title :
Complexity
Pages :
26-42
Publisher :
Wiley
Publication date :
2012
ISSN :
1076-2787
English keyword(s) :
Information content
Bennett's logical depth
Algorithmic complexity
Image classification
Algorithmic randomness
Bennett's logical depth
Algorithmic complexity
Image classification
Algorithmic randomness
HAL domain(s) :
Sciences de l'environnement/Biodiversité et Ecologie
Informatique [cs]/Traitement des images [eess.IV]
Informatique [cs]/Traitement des images [eess.IV]
English abstract : [en]
We present a method for estimating the complexity of an image based on Bennett's concept of logical depth. Bennett identified logical depth as the appropriate measure of organized complexity, and hence as being better ...
Show more >We present a method for estimating the complexity of an image based on Bennett's concept of logical depth. Bennett identified logical depth as the appropriate measure of organized complexity, and hence as being better suited to the evaluation of the complexity of objects in the physical world. Its use results in a different, and in some sense a finer characterization than is obtained through the application of the concept of Kolmogorov complexity alone. We use this measure to classify images by their information content. The method provides a means for classifying and evaluating the complexity of objects by way of their visual representations. To the authors' knowledge, the method and application inspired by the concept of logical depth presented herein are being proposed and implemented for the first timeShow less >
Show more >We present a method for estimating the complexity of an image based on Bennett's concept of logical depth. Bennett identified logical depth as the appropriate measure of organized complexity, and hence as being better suited to the evaluation of the complexity of objects in the physical world. Its use results in a different, and in some sense a finer characterization than is obtained through the application of the concept of Kolmogorov complexity alone. We use this measure to classify images by their information content. The method provides a means for classifying and evaluating the complexity of objects by way of their visual representations. To the authors' knowledge, the method and application inspired by the concept of logical depth presented herein are being proposed and implemented for the first timeShow less >
Language :
Anglais
Popular science :
Non
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