A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
A relevance feedback mechanism for content-based image retrieval
Information Processing and Management: an International Journal
Indoor-Outdoor Image Classification
CAIVD '98 Proceedings of the 1998 International Workshop on Content-Based Access of Image and Video Databases (CAIVD '98)
Distinguishing photographs and graphics on the World Wide Web
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
PicToSeek: combining color and shape invariant features for image retrieval
IEEE Transactions on Image Processing
Image classification for content-based indexing
IEEE Transactions on Image Processing
Categorization of web pages - Performance enhancement to search engine
Knowledge-Based Systems
Combining multiple modes of information using unsupervised neural classifiers
MCS'03 Proceedings of the 4th international conference on Multiple classifier systems
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Annotating images with a description of the content can facilitate the organization, storage and retrieval of image databases. It can also be useful in processing images, by taking into account the scene depicted, in intelligent scanners, digital cameras, photocopiers, and printers. We present here our experimentation on indoor/outdoor/close-up content-based image classification. More specifically, we show that it is possible to relate low-level visual features to semantic photo categories, such as indoor, outdoor and close-up, using tree classifiers. We have designed and experimentally compared several classification strategies, producing a classifier that can provide a reasonably good performance on a generic photograph database.