Color invariant for person images indexing

Muselet, Damien; Macaire, Ludovic; Postaire, Jack-Gérard; Louahdi, Khoudour

Type de document :

Communication dans un congrès avec actes

Titre :

Color invariant for person images indexing

Auteur(s) :

Muselet, Damien [Auteur]
Laboratoire d'Automatique, Génie Informatique et Signal [LAGIS]
Macaire, Ludovic [Auteur]

LAGIS-SI
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Postaire, Jack-Gérard [Auteur]
LAGIS-SI
Louahdi, Khoudour [Auteur]
Laboratoire Électronique Ondes et Signaux pour les Transports [IFSTTAR/LEOST]

Titre de la manifestation scientifique :

Conference on Colour in Graphics, Imaging, and Vision

Ville :

Unknown

Date de début de la manifestation scientifique :

2002

Date de publication :

2002

Discipline(s) HAL :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]

Résumé en anglais : [en]

Many colored object recognition methods tend to fail when the incident illumination varies. In the context of image indexing, a method is presented, which does not depend on lighting conditions. A new approach for indexing ...
Lire la suite >Many colored object recognition methods tend to fail when the incident illumination varies. In the context of image indexing, a method is presented, which does not depend on lighting conditions. A new approach for indexing images of persons moving in areas in where the acquisition is monitored by color cameras is developed to cope with the variations of the lighting conditions. We consider that illumination changes can be described using a simple linear transform. For comparing two images, we transform the target one according to the query one by means of an original color histogram specification based on color invariant evaluation. For the purpose of indexing, we evaluate invariant color signatures of the query image and the transformed target image, through the use of the color co-occurrence matrices. Results of tests on real images are very encouraging, with substantially better performance than those of other methods tested.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

Color invariant for person images indexing BibTeX CSV Excel RIS

Color invariant for person images indexing

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