Automatic Image Annotation Using Decision Trees and Rough Sets

The process which attaches label to a digital image by understanding the contents of image is termed as Automatic Image Annotation (AIA). Color and texture are the prominent features of a digital image. The content based image understanding is possible by using the feature strength of color and texture of an image. A classifier is designed using Decision Trees (DT) and Rough Sets (RS) to tag untagged images. Rough Set Exploration System (RSES) is used to develop decision tree and rough set based classifiers for classification of Corel images. In this paper, the result obtained using these classifiers are presented and discussed. Using rough sets cent percent accuracy is achieved for dinosaur images while for flower, horses and mountain categories the results are improved.