Abstract:
Annotation is an effective way to make image categorization and retrieval efficient. An effective method for image annotation is to decompose the problem into several ind...Show MoreMetadata
Abstract:
Annotation is an effective way to make image categorization and retrieval efficient. An effective method for image annotation is to decompose the problem into several independent single-label problems, but this ignores the correlations among different labels. In this paper, an image annotation system is proposed, that automatically annotates images by combining label correlation mining and visual similarity between the images. This method extracts the visually similar images from a collection of multi labelled images by using Content Based Image Retrieval (CBIR). Then the labels of resulted images are label correlated by using GLC (Grading based Label Correlation) algorithm and the correlated labels are assigned to the image. The proposed framework is applied to IAPR -TC image data sets. Experimental results of this approach indicate that the annotation is effective.
Published in: 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Date of Conference: 22-25 August 2013
Date Added to IEEE Xplore: 21 October 2013
ISBN Information: