Image region entropy: a measure of "visualness" of web images associated with one concept

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. Categories and Subject Descriptors I.4 [Image Processing and Computer Vision]: Miscellaneous General Terms Algorithms, Experimentation, Measurement Keywords image annotation, probabilistic image selection, Web image mining

• Type: Conference
• Year: 2005
• Where: MM
• Authors: Keiji Yanai, Kobus Barnard
• Keywords: Automatic Image Annotation, Image, Image Annotation, MM 2005