VISUAL 2000: Advances in Visual Information Systems pp 419-429 | Cite as
Integrating Visual and Textual Cues for Image Classification
Abstract
In this paper, we study computational models and techniques to merge textual and image features to classify images on the World Wide Web (WWW). A vector-based framework is used to index images on the basis of textual, pictorial and composite (textual-pictorial) information. The scheme makes use of weighted document terms and color invariant image features to obtain a highdimensional image descriptor in vector form to be used as an index. Experiments are conducted on a representative set of more than 100.000 images down loaded from the WWW together with their associated text. Performance evaluations are reported on the accuracy of merging textual and pictorial information for image classification.
Keywords
Synthetic Image Color Saturation Color Ratio Composite Information Pictorial InformationPreview
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