Multiscale Anisotropic Texture Analysis and Classification of Photographic Prints: Art scholarship meets image processing algorithms

Autor: Béatrice Vedel, Andrew G. Klein, Stéphane Jaffard, Pierre Borgnat, Paul Messier, Jim Coddington, Patrice Abry, Stéphane Roux, Nicolas Tremblay, Herwig Wendt, Lee Ann Daffner
Přispěvatelé: Centre National de la Recherche Scientifique - CNRS (FRANCE), Ecole Normale Supérieure de Lyon - ENS de Lyon (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Université Paris Est Créteil Val de Marne - UPEC (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Université Claude Bernard-Lyon I - UCBL (FRANCE), The Museum of Modern Art - MoMA (USA), Université de Bretagne Sud - UBS (FRANCE), Western Washington University - WWU (USA), Yale University (USA), Laboratoire d'Analyse et de Mathématiques Appliquées - LAMA (Paris, France), Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Signal et Communications (IRIT-SC), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique (CNRS), Institute for the Preservation of Cultural Heritage, Yale University [New Haven], Western Washington University (WWU), Laboratoire d'Analyse et de Mathématiques Appliquées (LAMA), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Fédération de Recherche Bézout-Université Paris-Est Marne-la-Vallée (UPEM), Université de Bretagne Sud - Vannes (UBS Vannes), Université de Bretagne Sud (UBS), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Université Paris-Est Marne-la-Vallée (UPEM)-Fédération de Recherche Bézout-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Toulouse - INPT (FRANCE), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Université Toulouse 1 Capitole (UT1)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP)
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Image processing
02 engineering and technology
Texture (music)
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Traitement des images
Image texture
Modern art
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Digital image processing
0202 electrical engineering
electronic engineering
information engineering
Photography
Traitement du signal et de l'image
Computer vision
Electrical and Electronic Engineering
Cluster analysis
Surface texture
Synthèse d'image et réalité virtuelle
ComputingMethodologies_COMPUTERGRAPHICS
Information retrieval
business.industry
Applied Mathematics
Anisotropic magnetoresistance
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
020206 networking & telecommunications
Vision par ordinateur et reconnaissance de formes
Intelligence artificielle
Spectral clustering
[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]
Optical surface waves
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Signal Processing
020201 artificial intelligence & image processing
Artificial intelligence
business
Art
Zdroj: IEEE Signal Processing Magazine
IEEE Signal Processing Magazine, Institute of Electrical and Electronics Engineers, 2015, 32 (4), pp.18-27. ⟨10.1109/MSP.2015.2402056⟩
IEEE Signal Processing Magazine, 2015, 32 (4), pp.18-27. ⟨10.1109/MSP.2015.2402056⟩
IEEE Signal Processing Magazine, Institute of Electrical and Electronics Engineers, 2015, 32 ( 4), pp.18-27. ⟨10.1109/MSP.2015.2402056⟩
ISSN: 1053-5888
Popis: International audience; Texture characterization of photographic prints can provide scholars with valuable information regarding photographers? aesthetic intentions and working practices. Currently, texture assessment is strictly based on the visual acuity of a range of scholars associated with collecting institutions, such as museum curators and conservators. Natural interindividual discrepancies, intraindividual variability, and the large size of collections present a pressing need for computerized and automated solutions for the texture characterization and classification of photographic prints. In the this article, this challenging image processing task is addressed using an anisotropic multiscale representation of texture, the hyperbolic wavelet transform (HWT), from which robust multiscale features are constructed. Cepstral distances aimed at ensuring balanced multiscale contributions are computed between pairs of images. The resulting large-size affinity matrix is then clustered using spectral clustering, followed by a Ward linkage procedure. For proof of concept, these procedures are first applied to a reference data set of historic photographic papers that combine several levels of similarity and second to a large data set of culturally valuable photographic prints held by the Museum of Modern Art in New York. The characterization and clustering results are interpreted in collaboration with art scholars with an aim toward developing new modes of art historical research and humanities-based collaboration.
Databáze: OpenAIRE
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