Low- and High-level Image Annotation Using Fuzzy Petri Net Knowledge Representation Scheme

Abstract

In order to exploit the massive image information and to handle overload, techniques for analyzing image content to facilitate indexing and retrieval of images have emerged. In this paper, a low-level and high-level image semantic annotation based on Fuzzy Petri Net is presented. Knowledge scheme is used to define more general and complex semantic concepts and their relations in the context of the examined outdoor domain. A formal description of hierarchical and spatial relationships among concepts from the outdoor image domain is described. The automatic image annotation procedure based on fuzzy recognition and inheritance algorithm, that maps high-level semantics to image, is presented together with experimental results.