Image region entropy
Keiji Yanai, Kobus Barnard · 2005
We propose a new method to measure visualness of concepts, that is, what extent concepts have visual characteristics. To know which concept has visually discriminative power is important for image annotation, especially automatic image annotation by image recognition system, since not all concepts are related to visual contents. Our method performs probabilistic region selection for images which are labeled as concept X or non-X, and computes an entropy measure which represents visualness of concepts. In the experiments, we collected about forty thousand images from the World-Wide Web using the Google Image Search for 150 concepts. We examined which concepts are suitable for annotation of image contents.