Content Based Image Retrieval (CBIR) is a widely adopted method for retrieving images from unannotated databases which are similar to a given query image. Usually images are indexed on the basis of low level features that can be automatically computed from the image visual content. Object detection and classification is a mandatory requirement for systems aiming at deriving semantic descriptions typically used by hymans to understand images. In this paper a novel approach is presented for object classification wihich is based on the extension of COMPASS, a CBIR system developed at ITC-irst. The experimental results are illustrated along with a comparison with a SVM classification approach recently proposed
CBIR techniques for object recognition
Andreatta, Claudio
2004-01-01
Abstract
Content Based Image Retrieval (CBIR) is a widely adopted method for retrieving images from unannotated databases which are similar to a given query image. Usually images are indexed on the basis of low level features that can be automatically computed from the image visual content. Object detection and classification is a mandatory requirement for systems aiming at deriving semantic descriptions typically used by hymans to understand images. In this paper a novel approach is presented for object classification wihich is based on the extension of COMPASS, a CBIR system developed at ITC-irst. The experimental results are illustrated along with a comparison with a SVM classification approach recently proposedI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
