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Proceedings Paper

Semantic classification of business images
Author(s): Berna Erol; Jonathan J. Hull
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Paper Abstract

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

Paper Details

Date Published: 16 January 2006
PDF: 8 pages
Proc. SPIE 6073, Multimedia Content Analysis, Management, and Retrieval 2006, 60730G (16 January 2006); doi: 10.1117/12.643463
Show Author Affiliations
Berna Erol, Ricoh California Research Ctr. (United States)
Jonathan J. Hull, Ricoh California Research Ctr. (United States)

Published in SPIE Proceedings Vol. 6073:
Multimedia Content Analysis, Management, and Retrieval 2006
Edward Y. Chang; Alan Hanjalic; Nicu Sebe, Editor(s)

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